Advances in Engineering Research and Application

This paper presents the results of a cost optimization problem to determine the optimum partial gear ratios of a two-stage helical gearbox with the second-stage double gear-sets. To accomplish the task, a simulation experiment was designed and solved by computer programming and applying the Minitab R18 software and the Taguchi method. The influence of the main design parameters as well as cost components on the optimal partial gear ratio of the first stage was investigated. In addition, a regression formula to calculate the optimal partial ratio has been introduced.

Fuzzy controller applications have become increasingly common in our lives, ranging from consumer products such as cameras, washing machines, and cars to industrial products including robots, subway trains, medical instruments, and home appliances. In our research, we apply and demonstrate the fuzzy controller on Unmanned Aerial vehicles (UAVs) for takeoff and landing purposes. Different from conventional controllers, the controller of fuzzy is not based on a mathematical model of the system. It is a form of intelligent control by experiment to adjust parameter control to be good for the system. By implement of UAV system, we enable to determine the rule of fuzzy control. Addition, we will show the performance of UAV by the algorithm of the fuzzy controller on LabVIEW. The outcomes presented highlight positive and useful aspects.

Induction motors are the most frequently used electrical motor in high-performance drive systems. The vector and sensorless speed control schemes of induction motors usually require exact values of motor parameters to obtain the robust control. This paper proposes an effective offline estimation of the equivalent circuit parameters of squirrel-cage three-phase induction motors using time-varying stator voltage and current with different load torques. The relationship between the input impedance and the slip rate can be expressed as a fractional polynomial. Based on conditions for obtaining the minimum of the objective functions, the motor electrical parameters can be conveniently estimated. The mechanical parameters of the motor can be derived by using determined electrical parameters and motor dynamic simulation using MATLAB/Simulink. The main advantage of this method is that it could facilitate us to gain the optimal values of the motor parameters without the need of any initial values. In addition, the effectiveness of the proposed method can be validated by a low-cost experimental system.

The rotary inverted pendulum (RIP) is a classical and underactuated system with two degrees of freedom. In this paper, we concentrate on addressing the swing up and stabilization of the rotary inverted pendulum, which are its two fundamental issues. In the beginning, we proceed to model the system. The two problems described previously are then solved by an energy sliding mode controller (ESMC). The effectiveness of the controller has also been verified through simulation results under the influence of external disturbance.

The paper studies a robust adaptive fast terminal sliding mode controller (FTSMC) based on a radial basis function neural network (RBF NN) for a dual-arm robot manipulator system that coordinates the motion of the general object. First, kinematics, a general dynamic model of the system consisting of manipulators and the object, is inferred about the position and direction of the object as the states of the derived model. Second, an FTSMC method is designed, followed by the construction of two RBF systems: one approximates uncertainties and external disturbances, and the other estimates the force applied to the object according to the object’s uncertainty model. Next, the Lyapunov theory is employed to demonstrate the stability of the closed-loop system and derive the adaptation laws for RBF NN. Finally, simulation results of the dual-arm robot system with three degrees of freedom (3-DOF) manipulators are presented to illustrate the effectiveness of the proposed method.

Nowadays, axial flux permanent magnet generators have been widely used in practice, such as: electric vehicles, renewable energy (e.g., wind energy, submersible energy), because they have advantages of the high working efficiency, high power density and low noise. In particular, its structure is simple in comparison with normal generators. Moreover, the structure of these generators is usually a type of disc, with the larger diameter rotor. Thus, it is very suitable for electric drives of the high torque and low speed. Otherwise, in order to increase the power supply, it can be used the multi-disc making more stages together. In this research, the main dimensions of the two generators have been successfully computed and analytically designed and the influence of armature reactions of axial flux permanent magnet generators with different loads is proposed via a finite element method.

Lotus silk is one of the rarest fabrics in the world. It is produced only in some Asian countries such as Cambodia, Myanmar, and, more recently, Vietnam. Taking silk from thousands of lotus stems is a very sophisticated and hard job. Extracting enough lotus silk for one scarf can take two months, and the final product can cost ten times as much as regular silk. Thus, lotus silk-made products are usually very expensive. With the aim of improving the productivity while preserving the traditional craft, this paper introduced the first lotus fiber extracting machine in the world.

The main objective of this paper is to investigate the effects of operating conditions of a mining dump truck with hydro-pneumatic suspension system (HPSs) on road surface friendliness, a three-dimensional vehicle-road coupled dynamic model of a mining dump truck with 11 degrees of freedom (DOF) is set up to investigate. The dynamic load coefficient (DLC) is chosen as objective function. The different operating conditions such as road surface roughness, vehicle speed and vehicle body mass are investigated through DLC value. The study results show that the vehicle operating conditions have a great influence on the road friendliness. The study results are the theoretical basis to optimize the design of the suspension system for off-road vehicles.

The objective of this article is to report the research results of designing electric wheelchair that can climb stairs. The study focuses on innovating and developing mechanical transmission assemblies of the stair climbing structure. Observing kinetics, dynamics and simulating the wheelchair motion are done by a professional software. Manufacturing and testing are implemented at Vinh Long University of Technology Education.

Despite the applicability in machining processes, current polygonal holes are manufactured by stamping but not by cutting. This will raise the required components’ price and influence the machining procedure for mechanical products. This paper proposes a concept method for machining parts with polygonal cross-section holes by cutting. Based on the motion of gear transmission in constructing Epitrochoid curves, a unique mechanism to control the position of straight groove drills bit to machines polygons’ holes is presented. Numerical calculations have been built to allow the detection of optimized machining parameters. Results from the study show that polygons holes machined from the new method can be applied in machining multiple types of polygonal without replacing cutting bits.

This paper presents the results of a multi-criteria decision-making (MCDM) study when CBN grinding SKD11 tool steel. In this study, the MOORA method was applied to solve the MCDM problem and the Entropy method was used to determine the weight of criteria. Two criteria including the surface roughness (RS) and the material removal speed (MRS) were selected for the problem. In addition, an experiment with design L18 (61 + 33) using Taguchi method was conducted. Four input parameters including the depth of dressing cut aed (mm), the wheel speed Rpm (rpm), the feed rate Fe (mm/min), and the wheel diameter d (mm) were investigated. According to the study's findings, the best experimental setup was proposed.

A multi-objective optimization study for CBN grinding SKD11 tool steel on a CNC milling machine is presented in this paper. In this work, two objective functions consisting of minimizing surface roughness (SR) and maximizing material removal speed (MRS) were considered. Four input factors dressing cut depth aed (mm), wheel speed Rpm (rpm), feed rate Fe (mm/min), and wheel diameter dw (mm) were investigated. The effects of the variables on the multi-objective function were assessed. Furthermore, an optimal set of input process parameters was suggested.

This paper aims to determine the optimal gear ratios of a helical worm gearbox in order to achieve the smallest gearbox volume. To solve this problem, a simulation experiment is designed and carried out. In the experiment, four main input factors including the total gearbox ratio, the coefficient of wheel face of stage 2, the allowable contact stress of stage 2, and the output torque were investigated. The effect of input factors on optimal gear ratios was evaluated. A regression formula for determining the optimal gear ratio has also been proposed.

Fabric waste treatment of the textile industry is a matter of current concern. Fabric shredding machines are used to shred fabrics for fuel combustion or recycling. In the process of working, the cutter is gradually worn, affecting the working ability of the machine. When the tool wears to the limit value corresponding to one cycle of tool life, the machine must stop working to change the tool. The fabric shredding efficiency and productivity of these machines are highly dependent on the tool life of the cutters. This paper presents a study on tool wear and tool life of cutters of fabric shredding machines. The influence of factors such as cutting speed, cleanliness or soiling of the input fabric on tool life is investigated for two types of tool materials as SKD11 steel and YG9C sintered tungsten carbide. From this, an optimal model to achieve the maximal productivity in a tool life cycle has been developed. Through optimization problem solving, optimal cutting speeds for specific cases have been determined.

Following the Model-Driven Architecture (MDA) approach, we have modeled and implemented planar trajectory planning and tracking controllers for Autonomous Underwater Vehicles (AUVs). This model covers all steps including the requirements management, analysis, design, and implementation to conveniently realize controllers for most standard AUV platforms. It also allows the designed elements to be customizable and re-usable in the development of new control applications for various AUVs. The paper describes step-by-step the development lifecycle of planar trajectory-tracking controllers for AUVs. Based on this proposed model, a horizontal planar trajectory-tracking controller of a low-cost turtle-shaped AUV was developed and taken on trial trips with good feasibility.

Recently, pneumatic artificial muscle (PAM) has been widely used in rehabilitation systems. These kinds of soft actuators are often used in an antagonistic configuration which allows conversion of longitudinal direction to rotating movements. This paper focuses on modeling and tracking control of a PAMs’ antagonistic configuration. The mathematical model of the antagonistic actuator is built based on the physical structure of a single PAM first. After that, an active disturbance rejection control method is employed for trajectory tracking purposes. Finally, the mathematical model and proposed control strategy are verified by experiments with and without a load.

Since introduced in 1990, the Hedge-algebras theory has been effectively applied to many theoretical and practical problems in different fields. This paper presents an approach for optimizing the controller based on the Hedge-algebras theory. In which the design variables include the parameters for building the Normalization and De-Normalization diagrams and the reference intervals of the state and control variables. This approach is applied to a building model subjected to earthquake loads. The objective functions are to minimize the system’s maximum relative displacement and absolute acceleration. The simulation results show that the optimal parameters make the controllers more efficient than controllers in published studies. In addition, the approach in the paper allows determining the controller parameters suitable for the investigated model instead of calculating them by a trial and error method. The approach in this study can be developed to design optimal controllers based on the Hedge-algebras theory for different mechanical models.

This paper proposed an enhanced hybrid Jaya algorithm, called AEHJ. The proposed AEHJ is a new improvisation of the Jaya algorithm (Jaya) and the differential evolution algorithm (DE) with two modifications. Firstly, the local search is improved by using DE/best/1, DE/best/2, and Jaya operators. Secondly, an elitist selection approach is used for choosing the best solution for the next population. For validating the feasibility of AEHJ, the well-known benchmark example of size optimization for a 10-bar truss is performed.

This paper presents the research results on manufacturing turbine blades in turbocharger machined on Haas VF2 module TRT 160 5-axis CNC milling machine and by 3D printing technology on Metal 3D printer HBD-280 series with the same material AlSi10Mg. The research sample is the compressed turbine blades in the HX40W turbocharger mechanism. CAD data files for machining programming and 3D printing of turbine blades are scanned from an ATOS Core 80 scanner with GOM and Geomagic Design X softwares. Some specifications of the two manufacturing methods are also presented. Research results show that the error of average diameter and surface roughness of 3D printing technology are larger than those ones of machining on a CNC milling machine while mechanical properties are lower. This shortcoming can be overcome by heat treatment to improve particle organization and mechanical properties.

Optimal cascade reservoir scheduling is a complex problem related to the broad interests of society, economy, and environment. This study proposes a solution for dispatching cascade reservoir operation optimization based on the multi-objective water cycle algorithm (MWCA). Search strategies for confluence, diversion, seepage, evaporation, and rainfall are established in the MWCA by simulating the natural water cycle process. A relative gravity mechanism under multi-objective is constructed to achieve an adequate search for optimal solutions. In the simulation section, the calculation results of the proposed approach are compared with the other methods in the literature, e.g., particle swarm optimization (MOPSO) and the genetic algorithm (NSGA-II). Compared results show that MWCA is superior to other algorithms in calculation diversity and an effective solution to the multi-objective optimal scheduling problem of cascade reservoir groups.

This paper studied the insulation characteristics of C2F6-N2 mixture based on the electron transport coefficients. The electron transport coefficients in C2F6-N2 mixture were calculated using Monte Carlo method and the electron collision cross section set for C2F6 and N2 molecules. The present results, especially the calculated limiting field strength in C2F6-N2 mixtures, will be helpful for the purpose of searching for suitable candidate for replacement of SF6 gas.

Machining of CFRP composites are usually accompanied by appearing defects induced in the machined surface. These kinds of damage are crucially evaluated in both qualitative and quantitative aspects. There have been few techniques which can meet two requirements so far. In this study, a noncontact optical method will be utilized to consider both quantitative and qualitative assessment of machining quality. Multidirectional CFRP plates are edge trimmed without lubricant. The variation of surface damage levels observed by optical method is analyzed. Moreover, areal roughness parameter, Sa, is chosen as an indicator for quantitatively evaluating machined surface. The analysis of tool wear mechanism is also conducted to show the advantages of the optical method for the machined fibrous composite surfaces.

The goal of this paper is to investigate a controller that enables not only to reject the anti-torque but also to minimize the energy consumption of a coaxial BLDC motor propelling for underwater vehicles. First, a structure of the coaxial BLDC motor with two counter-rotating rotors is introduced. Then, dynamic mathematical modeling of the BLDC motor is expressed in order to realize the proposed controller, a free chattering sliding mode control approach is toward the speed equal to two rotors in the opposite direction. To optimize the energy, a linear quadratic regulator (LQR) based control law combined with the sliding mode controller is proposed. Finally, the proposed controller is evaluated through simulation results.

The results of a study on determining the best input process parameters for dressing process in internal grinding SKD11 tool steel to achieve minimal surface roughness (RS) and maximum wheel life (T) all at the same time are presented in this paper. To accomplish this, the EDAS (Evaluation based on Distance from Average Solution) method was applied to solve the multi-criteria decision-making (MCDM) problem. Besides, the Entropy method was used to calculate the weights of the criteria. In addition, six input parameters were tested: coarse dressing depth, coarse dressing passes, fine dressing depth, fine dressing passes, non-feeding dressing, and dressing feed rate. The Taguchi method and an L16 orthogonal array were used to design this experiment. The best dressing mode for internal cylindrical grinding has been proposed based on the findings of the study.

A lift table is a very common piece of equipment in industry and production. This device uses a scissors mechanism to lift goods or people. There are numerous schemas (or diagrams) for the scissors mechanism. With the same set of input parameters, each schema will produce a different set of output responses. As a result, to achieve optimum design of a lift table, it is critical to determine the best scheme. This paper presents the findings of a study that used multi-criteria decision making (MCDM) technique to determine the best scheme for designing a lift table to meet two criteria at the same time: minimum lifting time and maximum lifting force. To accomplish this, nine different diagrams of the scissor lifting mechanism were analyzed using the Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) method for solving the MCDM problem and the Method based on the Removal Effects of Criteria (MEREC) for the calculation of the weights of criteria. Finally, the best lift table design scheme has been proposed.

A scissor lift table is a valuable piece of industrial equipment. This device is used to lift objects or people. The double lift tables were used to achieve the extra reach for this equipment. There are numerous schemas for double lift tables in practice. Each schema will produce different values of output results when given the same set of input factors. As a result, determining the best scheme is critical when designing an optimal double lift table. The purpose of this paper is to present a study on multi-criteria decision making (MCDM) to determine the best scheme for designing a double lift table that meets two criteria at simultaneously: minimum lift time and maximum lift force. To gain this, nine different double lift table schemas were analyzed using the Multi-objective Optimization Ratio Analysis (MOORA) method for solving the MCDM problem and the Entropy method for calculating criteria weights. Finally, the best design scheme for a double lift table has been proposed.

The goal of this research is to find the best process input parameters in wire-electrical discharge machining (wire-EDM) when processing 90CrSi tool steel. The TOPSIS method was used as a tool in this study to solve the MCDM problem. Furthermore, the MEREC method is employed to compute the weights on the output parameters of the experiment result. According to the results of this work, experiment No. 19 is the best experimental setup, with the following input parameters: the cutting voltage VM = 9 (V), the pulse on time Ton = 12 (s), the pulse off time Toff = 18 (s), the servo voltage SV = 35 (V), the wire feed WF = 8 (mm/min), and the feed speed SPD = 4.5 (mm/min).

This paper describes the results of a study on multi-criteria decision-making (MCDM) in cylindrical external grinding SKD11 tool steel to identify the best input process parameters for dressing process in external grinding in order to achieve minimal roundness (R) and maximum wheel life (T) at the same time. To accomplish this, the MCDM problem was solved using the WASPAS (Weighted Aggregates Sum Product Assessment) method, and the weights of criteria were calculated using the Entropy method. In addition, an experiment was conducted with six input process factors: fine dressing depth, fine dressing passes, coarse dressing depth, coarse dressing passes, non-feeding dressing, and dressing feed rate. The Taguchi method and an L16 orthogonal array were also used to design the experiment. The experimental output results were measured and fed into the MCDM problem, including the roundness and wheel life. The best dressing mode for external cylindrical grinding has been proposed based on the findings of this study.

This research presents an adaptive hierarchical sliding mode control approach based on fractional order derivatives and radial basis function neural networks for an uncertain 2D Ballbot system. Instead of using fixed integer order derivatives as usual, fractional order derivatives are used because of the possibility of adjustment. To estimate the unknown dynamic model, a radial basis function neural network is used. The control law is constructed from a candidate of the Lyapunov function in order to assure the stability of sliding surfaces, and an updated law for neural network weight matrices is derived from it. Simulation findings show that the suggested control technique is effective, resulting in a lower swing and more precise location tracking as anticipated.

The suspension system in a car plays an important role in ride comfort, road holding, and ride safety, as it transmits all forces from the road to the vehicle body. The dynamics of the suspension system not only influence considerably the handling capabilities of the car but also prevent physical fatigue of driver and passengers and reduce the rate of fatality in traffic accidents. This paper concerns with an active suspension system in a half-car model, if we consider the left and right side of the car is symmetrical. We proposed a backstepping controller for this system with a reference trajectory which improves the ride comfort of the people sitting in the car. The system’s zero dynamics are mathematically proved. Control quality is validated by simulations in different scenarios and compared to the passive suspension system in MATLAB/Simulink.

In this study, the critical capacity of concrete-filled steel tubes (CFST) under axial compression is investigated through a machine learning model (BCM-NN) that is a combination of Balancing Composite Motion Optimization (BCM) and Artificial Neural Network (NN). To develop the model, a database of experimental results is gathered from literature works. Such database includes variables related to the CFST geometry parameters and its mechanical behavior. Quality assessments namely coefficient of determination (R2) and Root Mean Square Error (RMSE) are used to evaluate the performance of the proposed model. The value range of each model parameter has also been studied in this work. The obtained results show that the hybrid BCM-NN model produced great performance in predicting the critical load of CFST compared to conventional neural network algorithms.

Toward 2030, 20% of existing buildings and all new construction would have to be zero-carbon ready for reaching the global goal of carbon neutrality by 2050. As a member state of UNFCCC, Vietnam has come up with mechanisms and policies to ensure compliance with strong commitments at COP26. However, energy efficiency design strategies for new construction would not guaranty the energy reduction if buildings were not appropriately operated. To contribute the objective of energy savings and lowering the building’s operational costs, this paper presents a Machine Learning approach for an office building, located in Danang, to forecast the power demand based on time, weather conditions and historical energy consumption. For discovering energy consumption pattern and correlation between features, exploratory data analysis has been performed to initially investigate data sets and summarize their main characteristics. After selecting features that have strong relationship with the target, the power demand of this office building has been predicted using different Machine Learning methods. Forecasting results will be compared to define the relevant method.

This paper introduces a study on calculating optimum Wire Electrical Discharge Machining (Wire-EDM) factors when cutting arc of SKD11 tool steel to get the maximum Material Removal Rate (MRR). Seven input parameters were examined in this work: the pulse on time, the pulse off time, the cutting voltage, the serve voltage, the cutting speed, the wire feed, and the arc radius. The effect of these factors on the MRR of the Wire-EDM process was investigated. Furthermore, optimal input factors for achieving the highest MRR were suggested. It was also reported that the optimal input parameters were appropriate for use.

The goal of this study is to find the best main design parameters of a two-stage helical gearbox in order to achieve the lowest gearbox mass. The gear ratio of the first stage, the coefficient of wheel face width of stages 1 and 2, and the allowable contact stress of stages 1 and 2 were all taken into account in this work to determine their optimum values. To achieve the goal, a simulation experiment was designed and implemented by a computer program. The Minitab R19 software was also used to analyze the experimental results. The impact of key design factors on gearbox mass was assessed. The best values for these parameters were also proposed.

Significant success of Deep learning (DL) in extracting features from big data which led to an explosion of Artificial Intelligence (AI) applications. However, most of those AI systems lack transparency and interpretability due to the black-box nature of DL architecture, which causes major trust-related problems in AI applications where validation is essential. This necessitates the need for interpretable AI systems that can explain their decisions. In this view, this paper proposes a deep adaptive neuro-fuzzy inference system (Deep ANFIS), that combines fuzzy inference with DL architecture to provide a more comprehensible explanation of the decision processes. Deep ANFIS uses ANFIS based convolution units in convolutional neural networks (CNNs) architecture that allows approximating the complex non-linear problems using fuzzy if-then rules. To verify the performance of the proposed Deep ANFIS and analyze the essential features for classification, we perform experiments with COGNIMUSE dataset for emotion recognition.

This paper describes a multi-criteria decision making (MCDM) study that was conducted to determine the best input process factors for powder-mixed electric discharge machining (PMEDM) 90CrSi tool steel in order to achieve minimal surface roughness (RS), maximum material removal speed (MRS), and maximum electrode wear rate (EWR) all at the same time. To accomplish this, the MCDM problem was solved using the MABAC (Multi-Attributive Border Approximation Area Comparison) method, and the weights of the criteria were calculated using the MEREC (Method based on the Removal Effects of Criteria) method. In addition, five input factors were investigated: powder concentration, pulse-on time, pulse-off time, pulse current, and servo voltage. Furthermore, the experiment was designed using the Taguchi method with an L18 (21 + 34) orthogonal array. The best input process factors for PMEDM 90CrSi steel have been proposed based on the study's findings.

The purpose of this research is to determine the optimum main design parameters for minimizing the cross-section area of a two-stage helical gearbox. In this work, five main design parameters of the gearbox were taken into account to find their optimum values, including the gear ratio of the first stage, the coefficient of wheel face width of stages 1 and 2, and the allowable contact stress of stages 1 and 2. A simulation experiment was designed and implemented by a computer program to achieve the goal. Furthermore, the Minitab R19 software was used to analyze the experimental results. The impact of major design factors on cross-section area was assessed. The optimum values for these parameters were also suggested.

This paper is about the state of road safety in Vietnam, the accident rate indicators are given and latest measure for reducing the impact of accidents and suggestions to increase traffic flow - the use of Photo- and Video- Fixation system for fixing traffic violations. The purpose of this article is to improve the efficiency of this system and to improve the quality of traffic flow. In this case, enhancing the traffic monitoring camera system solves two major problems: increasing road safety by reducing the number of accident cluster, increasing the effectiveness of traffic organization by increasing traffic capacity and identifying traffic violations.

This paper presents the findings of a study on determining the best input dressing parameters for internal grinding SKD11 tool steel to achieve minimal surface roughness (RS), maximum material removal rate (MRR), and maximum wheel life (WL) simultaneously. To achive this, the multi-criteria decision-making (MCDM) problem was solved using the MABAC (Multi-Attributive Border Approximation Area Comparison) method. In addition, the MEREC (Method based on the Removal Effects of Criteria) method was applied to compute the weights of the criteria. Furthermore, six input parameters were investigated including coarse dressing depth, coarse dressing passes, fine dressing depth, fine dressing passes, non-feeding dressing, and dressing feed rate. The experiment was designed using the Taguchi method and an L16 orthogonal ar-ray. Based on the results of a study, the best input dressing factors for internal cylindrical grinding have been proposed.

This paper describes the findings of a multi-criteria decision-making (MCDM) study in CBN grinding Al6061 T6 to determine the best input process parameters to achieve both minimal surface roughness (SR) and maximum material removal speed (MRS). In order to do this, the WASPAS (Weighted Aggregates Sum Product Assessment) method was used to solve the MCDM problem, and the weights of criteria were calculated using the MEREC (Method based on the Removal Effects of Criteria) method. Furthermore, an experiment was carried out with four process input parameters containing wheel speed (WS), feed rate (Fe), depth of cut (aed), and down feed (Df). The experiment was designed by a 2-level 1/2 fraction type. The experimental output results, including the SR and MRS, were measured and supplied into the MCDM problem. Based on the findings of this study, the best input parameters for CBN grinding Al6061 T6 were proposed.

The partial gear ratio is an essential factor in gearbox design because it is directly related to the gearbox’s volume, size, and cost. A method for determining the optimum gear ratio u1 of a two-stage helical gearbox with the first-stage double gear set to achieve the lowest cost was presented in this work. To accomplish this, a simulation experiment was designed and run by an optimization program with the goal of minimizing gearbox costs. Ten input factors were considered in the experiment to determine their influence on the optimal gear ratio of the first stage u1. Finally, the proposed regression model is validated by calculating the difference between the experiment and response u1 using the residual evaluation distribution.

This paper presents the results of a multi-criteria decision-making (MCDM) study in powder-mixed electrical discharge machining (PMEDM) cylindrically shaped parts made of 90CrSi tool steel. In this study, five input factors including powder concentration, pulse duration, pulse off time, pulse current, and servo voltage were selected for the investigation. Besides, the Taguchi method was applied for the experimental design. Furthermore, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method was used to solve the MCDM problem in order to achieve both a low electrode wear rate (EWR) and a high material removal speed (MRS). The Entropy method was also used to compute the weights of the criteria. Based on the findings, the best solution for the MCDM problem in PMEDM cylindrically shaped parts was proposed.

Due to the rising number of car accidents involving drowsy or distracted drivers, it is essential to develop a system to detect these drivers’ behaviors. Multiple strategies were proposed and evaluated to determine whether the driver is in those driving states. Based on data collected from a surveillance camera and onboard diagnosis system, our research group has developed a method and system to recognize those abnormal behaviors and alert the driver to focus on driving. An onboard computer is used to evaluate the potential of the application system in an actual driving situation. The result shows that the system could operate effectively.

The creation and management of an intelligent waste sorting system using a robot arm are described in the study. This system comprises a 6DOF robot manipulator, a machine vision block, and a control unit for rubbish sorting using analytic pictures. The item will be recognized by the neural network using the YOLOv4 software. This technique detects and identifies various types and kinds of trash, including paper-based waste, metal waste, and plastic waste. Results of offline testing on a library of more than 600 untrained photos reveal that the trained model has an average classification accuracy of roughly 98.43%.

In this study, a numerical Discrete-Element-Modeling (DEM) model was created to analyze a displacement field to identify the shear behavior in a granular media. The resultant shear stress/normal stress ratio was compared to findings reported in the available literature to validate the DEM model. The simulation model's displacement field enabled analysis of the mechanical properties of the granular medium. Exploring the mechanical behavior of granular media under various boundary conditions and/or loadings may be helpful with the DEM model.

An autonomous vehicle is a fascinating and trendy topic from both research and practical perspectives. It can be said that this is a development tendency for future automobiles and attracts the attention and a substantial amount of finance from big automobile corporations worldwide. In terms of technology, driving a driverless car puts a great deal of pressure since there is only one control input (steering angle) that must simultaneously control the position and yaw angle of the vehicle. Moreover, the position of the vehicle over time is a function of the yaw angle. In order to solve the problem, this study proposes a new approach with the use of a dual-loop Proportional Integral Derivative (PID) controller combined with optimizing parameters based on the Particle Swarm Optimization (PSO) algorithm to improve the control performance. By simulating cars following given trajectories based on the car's kinematics and dynamics, the efficiency and feasibility of the work can be assessed. The numerical simulation results of both the established PID controller and PSO algorithm are given at the end of the presentation.

The results of a study on the influence of input factors on the material removal speed (MRS) in electrical discharge machining (EDM) cylindrical shaped parts made of SKD11 tool steel are presented in this paper. The Taguchi method was used to design the experiment and analyze the results to solve that problem. In addition, the input process factors such as the pulse time, the pulse off time, the current, and the serve voltage were investigated. In addition, Analysis of Variance (ANOVA) technique was used to assess the effect of the input factors on MRS. Furthermore, a set of optimal input factors for achieving the maximum MRS has been proposed.

This study numerically investigates the effect of multi-curve blade configuration on the performance of the optimized Savonius wind turbine. The simulation is performed utilizing a sequence of unsteady 2D computational fluid dynamics in the commercial software ANSYS Fluent 2021R2. The results state a high influence of the turbine performance on the multi-curve shape. The highest performance of the rotor is recognized on the blade configuration with the main profile made by a quarter circular R3* = 0.5 and a quarter elliptical section. For which, the power coefficient Cp is improved by 185.1% at the tip speed ratio (TSR) higher than 1.0 and up to 5.5% at TSR of less than 0.8, making this design better suited for wide working conditions over the previous configurations.

This study analyzes scientific basis of fuel-saving racing vehicles. Every year, Honda corporation organizes an Asian competition with the purpose of choosing a model of the most efficiency. Students representing Asian countries take part in this competition. Haui Super Cub's of Hanoi University of Industry has been highly appreciated in 2020 competition. The vehicle consumes 1352 km/liter.Research method includes: Using drag coefficient CD to analyze the affect of the air drag force LD to the fuel consumption SG and, analyzing the affect of the composite material to vehicle mass.The results of this research will be used to improve the car’s designing and building in following competitions.

Vibration is an important problem in automotive design and production process, particularly in passenger bus. There are some factors that affect the vibration behavior of the bus, one of which is the selection of main material for the body. This paper presents analyses on how the passenger bus body vibration behavior changes when composites are used as the main material. Finite Element Method in Ansys Workbench to conduct the analyses used. Comparing the frequency range and the magnitude of vibration in the two cases of using sheet metals and composites as the main material for the bus body. The results have contributed to the assisting apply of advanced materials in automotive design and manufacturing.

Nowadays, 3D printing technology is becoming more popular with various applications. 3D printing is also a potential process in tissue engineering applications for fabricating scaffold. The scaffold needs to have the proper structure and properties to initiate a favorable environment for cell growth and tissue generation. In this study, the customized direct powder extrusion based on screw extruder was developed and the influence of printing parameters including printing speed and temperature on characteristics of scaffolds from PCL powder was investigated. The result evaluation shows that the size of line width and pore size are significantly affected by printing parameters. The optimal printing conditions were obtained at print speed 6 mm/s, extrusion speed 50 rpm, and heating temperature of 100 ℃ to fabricate scaffolds from PCL powder materials. The results are the basis for further studies in optimizing the printing condition for PCL scaffolds based on direct powder extrusion.

The results of a study on the effect of the process parameters on the material removal speed (MRS) in CBN grinding Al6061 T6 are presented in this paper. To do this, four input parameters were investigated in the study: wheel speed (WS), feed rate (Fe), depth of cut (aed), and down feed (Df). The impact of these variables on the MRS of the grinding process was investigated. Furthermore, a regression model was proposed to determine the relationship between the input parameters and the MRS. It was also stated that the proposed model was suitable for use.

Due to the significant share of the induction motor (IM) in the global electricity consumption, the study of the IM and its drive systems in different power supply modes is the aim of this paper. This paper presents the effects of voltage unbalance considering the positive-sequence component on efficiency, power factor, torque ripple, and current total harmonic distortion of the direct matrix converter induction motor drive (DMCIMD). Simulation results have also shown that torque ripple and average current total harmonic distortion increase linearly with increasing voltage unbalance factor (VUF). In the case of voltage unbalance with positive-sequence voltage less than phase voltage, the increase of VUF reduces efficiency and increases the power factor of DMCIMD. Conversely, in the case of voltage unbalance with positive-sequence voltage greater than phase voltage, the increase in VUF increases efficiency and decreases the power factor of DMCIMD.

The paper presents a proposed hardware device for ECG signals measurement with an integrated remote system for signal automatic analysis to help doctors monitor health, diagnose cardiovascular diseases. This measuring device can transmit the ECG signals online to the server, The server is equipped with a software for analyzing ECG signals and classifying them to detect the arrhythmias using a RF (Random Forest) network. The Hermite basis functions were used to generate the feature vectors together with 2 time-based features: the last R-R period and the average of the last 10 R-R periods. The proposed solution was tested with ECG signals taken from databases MIT-BIH (Massachusetts Institute of Technology, Boston’s Beth Israel Hospital). Seven types of ECG beats were classified with an error of 2.28%. The proposed Random Forest algorithm works very fast, which makes it suitable for the requirement of quick classification of some cardiovascular diseases.

In this paper, analysis of the torque ripple and radial force reduction by different rotor pole designs of a three-phase 6/4 switched reluctance motor is presented. In order to improve torque performances by changing stator and rotor angles for three-phase switched reluctance motors, many papers have recently used the types of stator and rotor poles, with 6/4; 8/12; 18/12 and 24/18. Improvement of the average torque and torque ripple have influenced directly on rotor poles designs, because flux density distribution at the air gap will affect torque performance and radial forces. Several rotor tapped-skew poles have been calculated for the three-phase switched reluctance motor by the finite element method to give suitable results. The efficiency, average torque and torque ripples have been simulated and analyzed. A significant distribution of this research is to implement the skew-tap rotor pole with the optimal tap-angle for maximizing torque ripple and radial forces. The improvement of method is validated on the practical problem, with a switched reluctance motor of 30 kW.

A bridge crane, or 3D crane, is a classic research subject in the control field and is considered a typical example in the group of underactuated systems. This control problem is relatively fascinating and poses significant challenges when the number of control signals is larger than that of state variables to be controlled. Specifically, the task of the control algorithm is not only to ensure the correct tracking with the desired trajectory but also to reduce and quickly extinguish unwanted oscillations. In this study, we develop a controller for the system with a vertical-oscillation quenching capability, a problem that was rarely mentioned in previous studies. Based on the positive definite and the skewed symmetric characteristics of the matrices of the mathematical model, a controller is designed to guarantee the stability of the system according to Lyapunov criteria. Paralleling the convergence of the tracking errors, the horizontal and vertical oscillations of the cargo are suppressed. Simulation results are given at the end of the paper to investigate the effectiveness and feasibility of the entire study.

This paper proposes a new optimal approach to determine the location and size of the Energy Storage System (ESS) in transmission expansion planning (TEP). The proposed method combines two steps in sequence: the improved MinCut algorithm (IMCA) and the Genetic Algorithm (GA) algorithm to reduce the search space and time for finding the optimal solution satisfying many constraints. This algorithm reduces the computational volume significantly compared to previous algorithms and thereby shortens the calculation time leading to investors making timely and competitive ESS system investment decisions. The research results are applied in determining the position of the ESS in the IEEE 24-bus system, which shows the possibility of a solution to the TEP problem.

This paper presents and evaluates the method of order of large-scale unstable power systems using Modal truncation (MT), Balanced truncation (BT), Positive-real balanced truncation (PRBT), Balanced stochastic truncation (BST) and Linear-quadratic Gaussian balanced truncation (LQGBT). The results show that the LQGBT and BT algorithm has the smallest order reduction error. The MT method has the largest order of decreasing error. The BST algorithm gives the best time domain response. The PRBT method preserves the passivity of the original system. The simulation results show the advantages and disadvantages and the application range of step reduction methods.

The tank truck had stability very poor during movement due to affecting of internal vibration of the liquid in tank. So to assess the rollover stability of a circular tank truck in case of double lane change maneuver corresponding to each liquid level in the tank, the research investigated the load transfer ratio (LTR) value and the roll angle of suspension. The paper used the Lagrange method for the quasi-static model of the circular tank and the D'Alembert's principle for the roll model of the vehicle. Then the system of differential equations for rollover stability was built from the two models above. The simulation results showed that when the vehicle moves at a speed of 100 km/h corresponding to the liquid level height of 0.4, 0.8 m compared to the tank diameter, the vehicle was rolled causing danger to people and property. Therefore, during the tank truck operation, the driver should noted the vehicle movement speed and it is necessary to propose speed limit warning signs along the road.

Vietnam is a dense population country. As to Vietnam’s economic growth in the past years, energy has played an important role. With rapid urbanization and the improvement in people’s standard of living, the demand for energy will keep growing. Promoting saving and efficient use of energy prioritize of urban residents by implementation of energy-saving behaviors is the key to build a sustainable urban environment, and reduce carbon emissions. This study establishes a theoretical model of the factors affecting the energy-saving behavior of urban residents in Hanoi based on the Theory of Planned Behavior and research methodologies in economics and psychology. In this study, we used 300 questionnaires for Hanoi urban residents survey. The influence mechanism of energy-saving behavior of urban residents is clarified through a structural equation based on partial least squares (PLS-SEM). The result shows that factors such as subjective norm, perceived behavioral control, perceived usefulness of energy-saving technology have a direct effect on the intention to use energy-saving. This study did not find an impact relationship between attitude and intention to use energy saving. These results play an important part in the build of energy saving policies in urban Hanoi.

This paper introduces an H∞ optimal tracking controller for robot manipulators with saturation control torque, and disturbances based on a reinforcement learning (RL) method. The robot manipulators dynamics are transformed into a strict-feedback nonlinear system with input constraint, and disturbances. The feedforward control inputs are designed to transform a position tracking control problem into an H∞ optimal control problem. The constrained Hamilton–Jacobi–Isaac (HJI) equation is built, which is solved by the online RL algorithm using only a single neural network (NN) to reduce computational cost. Then the optimal control law with the input constraint and the worst disturbance law are determined. The concurrent learning (CL) technique is used to relax the demand for the persistence of excitation (PE) condition when updating the critic NN weights to global optimal values. The control performance is given in the comparative simulation results, showing the effectiveness of the proposed method.

In this paper, a brief overview on the Hybrid Energy Storage Systems (HESSs) is provided. In literature, different architectures are chosen to realize the HESSs, and they are based on the principal aim of the HESSs employment. In this paper, the most used HESS topologies are presented, with particular attention to the active, passive and semiactive topologies, highlighting their characteristics. To have a complete schematic idea of the HESSs application, a focus on the principal sizing methodologies is provided, distinguishing the conventional approaches and the advanced ones, exploiting their main applications. Together with a proper sizing, a correct power-sharing strategy is one of the HESSs key points. For this reason, several control strategies are described, focusing on the energy management control and on the underlying control.

The abstract should summarize the contents of the paper in short terms, i.e. 150–250 words. Magnesium (Mg) and its alloy continue developing in popularity since they are the most lightweight structural metallic materials. Mg alloys have several features that make them ideal for use as biodegradable prostheses in clinical practice. Despite having excellent properties, the greater application of Mg alloys is limited by various natural constraints, including a high degradation rate and hence loss of mechanical strength. In addition to basic alloying, surface treatment and functionality are prominent ways to improve resistance to corrosion for Mg alloys. This research belongs to the improvement in corrosion resistance of AZ31B Mg alloy by coating Zinc oxide (ZnO) and Silver (Ag) with the help of an RF magnetron sputtering system. A comparison of the degradation rate is made with and without coating. The degradation testing immersion test is done in Hank’s Solution, a simulated body fluid (SBF) type. The biodegradable behavior of AZ31B in SBF was examined for different immersing time intervals. The corrosion rate was found to be reduced when coated with Zinc oxide (ZnO) and Silver (Ag) with the help of RF magnetron sputtering. The coating also reduced the surface roughness of samples.

This paper presents a multi-objective study on internal grinding to achieve minimum surface roughness (SR) and maximum wheel life (WL) at the same time. This study looked at six input parameters: coarse dressing depth ar, coarse dressing time nr, fine dressing depth af, fine dressing time nf, non-feeding dressing n0, and dressing feed rate Sd. The effect of these parameters on the SR and WL of the grinding process was investigated. Furthermore, optimal input parameters to achieve SR and WL at the same time were proposed. It was also reported that the optimal set of input dressing parameters was appropriate for use.

This paper describes the results of a study to determine the optimal process parameters when Wire Electrical Discharge Machining (Wire-EDM) process was used to cut circular arcs of SKD11 steel. Several input parameters were considered in this study, including the pulse on time, the pulse off time, the cutting voltage, the servo voltage, the wire feed, the cutting speed, and the arc radius. The effects of these parameters on the surface roughness of the workpiece after cutting process were discovered. Furthermore, optimal process parameters for achieving the best surface finish were discovered. It was discovered that the best experimental mode was appropriate for use.

This paper presents the findings of a study on the influence of process parameters on surface roughness (SR) in CBN grinding when processing Al6061 T6. The study looked at four input parameters including wheel speed (WS), feed rate (Fe), depth of cut (aed), and down feed (Df). The effect of these variables on the grinding process's SR was evaluated. A regression model was also proposed in order to identify the relationship between the input parameters and the SR. It was also stated that the proposed model could be used.

The aim of the current study is to find the optimum set of WEDM parameters which can maximize the material removal rate when machining circular profile of hardened SKD11 steel. Six main parameters namely Cutting voltage, pulse on time, pulse off time, server voltage, wire feed, cutting speed have been investigated by using Taguchi technique. In order to find the significant level of WEDM process parameters, analysis of variance has been adopted. The results show that Toff has the most influence on MRR with 46.21%. Confirmation shows that the proposed process for optimizing is reliable and can be extended to WEDM machining of other hard work materials.

This paper proposes an intelligent controller for output tracking control for a completely uncertain two-state continuous stirred tank reactor (CSTR) with disturbance on input. This control method is established by combining the concept of iterative learning control (ILC) and a model-free disturbance estimator for compensating purpose. Hence, the created controller does not use the original nonlinear model of CSTR or linearize it around operating points as usual. In consequence, all unexpected performances, which are inevitability caused by switching the control between linear subsystems, are prevented. The effectiveness of proposed approach had been authenticated by an illustrative simulation.

The drive system using the large power AC motor to meet the heavy load requirements leads to difficulty both economically and technically. Using the large power means high manufacturing costs for a large-capacity inverter (controlled inverter for 3-phase synchronous motor). Therefore, it is necessary to propose solutions to control the drive system using two AC motors with a standard stiff shaft to reduce each motor's power and reuse the available motors in the system. This article presents the fuzzy adaptive control method capable of controlling load sharing for the drive system using two 3-phase synchronous AC motors with a common stiff shaft. This method meets the control performance requirements for the torque and speed of the drive system.

Internal combustion engines (ICEs) that use petroleum-based fuels are the most commonly used engine types in vehicles. During the operation of ICEs, a large amount of harmful emissions is generated, which are the leading causes that adversely affect the quality of the environment and human health. Moreover, over-reliance on fossil fuels leads to an imbalance between energy sources (electricity, solar energy, and new energy sources). In this paper, the author presents a method to use Ammonia to replace traditional fuel. Ammonia is one of the most promising carbon-free alternative fuels. High-octane, low-viscosity ammonia protects against detonation and is also an effective hydrogen carrier: 1.5 mol of hydrogen per mole of ammonia. For research purposes, a mathematical model has been built to describe the working process of ICE using Ammonia. The research results show that the feasibility of using alternative fuel Ammonia and the cycle specification of the internal combustion engine is significantly improved.

Two-dimensional simulations of laminar mixed convection in a square enclosure subjected to constant wall temperature with a heated rotating cylinder have been carried out. The enclosure is filled with non-Newtonian fluid. Due to the rotation of the cylinder, forced convection effects are set up along with the natural convection. The effect of different parameters, viz: Rayleigh number (103 to 106), and angular velocity on non-Newtonian fluid enclosed in a square enclosure are investigated. Observations are also made on the dynamic behavior of the flow features and temperature fields due to the rotation of hot cylinder inside a square enclosure. Overall, the present study focuses on how the rotating cylinder affects the thermo-fluid behavior of non-Newtonian fluids and quantifies heat transfer characteristics.

Currently, there are many researches to improve the efficiency and capacity of the vibrating screen. Usually, multi-slope vibrating screens use an unbalanced exciter to produce a circulating radial force of the same frequency on both drive shafts. This produces an alternating force in the direction of the exciter stand due to the circulation of the imbalance weights. The basic working parameters, such as the forces acting on the bearings of the drive shafts and the supporting springs, the amplitude, velocity, acceleration, and orbit of the screen surface, have an important role in the design of a vibrating screen. These parameters are usually determined by establishing a vibrating model and solving the technical vibrating problem. However, this method does not give high accuracy because it simplifies the vibration model of the screen. To make simulation results more accurate, this study builds a 3D model of the vibrating screen and uses a dynamic multi-body simulation to determine the basis working parameters of the screen. The correctness of dynamic simulation research is verified through experiment. This work would provide some guidance for designing and studying vibrating screen with flexible construction and working parameters.

As the irradiance changes, the current at the maximum power generating point (MPP) of the photovoltaic (PV) cell system fluctuates. But when the temperature changes, its voltage is affected more. In actual conditions when operating in a partial shade (PSC) condition, fluctuation of these two parameters makes it difficult to determine the global maximum power point tracking (GMPPT) accurately. The compatibility between the PV system topology and the algorithm plays an important role in improving the performance of the whole system. This paper proposes a PV module architecture combined with inverters and a standalone MPPT technique operating under non-uniform temperature and radiation conditions. A modified P and O algorithm with multiple inrush current values as an input parameter is simulated in the PSC. The research results in this paper have shown that the proposed solution not only has outstanding speed but also has the ability to significantly improve performance compared to published methods under the same operating conditions.

This paper present the results of a study on the application of the Multi-Criteria Decision Making (MCDM) technique to select the best input parameters in Wire Electrical Discharge Machining (WEDM) 90CrSi tool steel. In the study, the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method was used to solve the MCDM problem, and the Entropy method was used to calculate the weights of the criteria. In addition, six input parameters are required: the cutting voltage VM, the pulse on time Ton, the pulse off time Toff, the servo voltage SV, the wire feed WF, the feed speed SPD, and the workpiece cutting radius R. In addition, a 27–2 design experiment was carried out and a total of 32 different experimental setups were performed. The MCDM problem has been solved. The best experimental setup, according to the results of this work, is experiment no. 7 with the following input parameters: VM = 9 V, Ton = 12 s, Toff = 13 s, SV = 25 V, WF = 8 mm/min, SPD = 4.5 mm/min, and R = 9 mm.

This paper presents a multi-objective study on the determination of optimum dressing parameters for internal grinding. The aim of this study is to achieve minimum surface roughness (SR), maximum material removal rate (MRR) and maximum wheel life (WL) concurrently. To accomplish the stated goal, six input dressing parameters including coarse dressing depth ar, coarse dressing time nr, fine dressing depth af, fine dressing time nf, non-feeding dressing n0, and dressing feed rate Sd were taken into account. The effect of the parameters on the SR, MRR and WL of the grinding process was evaluated. Furthermore, the optimal input parameters to achieve the mentioned objectives were proposed. It was also reported that the proposal optimal dressing parameters were suitable for use.

Wireless sensor networks (WSNs) facilitate many applications in different fields and are well-known in both academic and industrial areas. The networks mainly include sensors, networking parts and a data processing center to collect data for a variety of purposes. However, the energy consumption problem in the networks is always a critical problem that many researchers are looking for good solutions. In this paper, we propose a data collection method that uses mobile sensors attached with bigger energy storages to collect data from static sensors. In addition, we propose a hybrid energy harvesting scheme to harvest energy from ambient environments to support static sensors to prolong the network lifetime. Some algorithms are provided to support the networks either with data collection or harvesting energy. We outline various possibilities for powering the gadgets with solar and RF energy gathering. In particular, all the circuits that are constructed using mathematical equations are offered. All of the network possibilities are clarified using simulation and experimental results. The outcomes are encouraging and useful.

Compact heat recovery systems require effective heat exchange process. Placing winglets on the gas side of finned-tube type heat recovery systems promotes bulk flow mixing. In this study, delta-shaped winglets are placed in the tube aft region. Under fixed operating conditions, winglets’ geometry is varied to assess the change in performance. The study considers winglets with four distinct aspect ratios (AR = 0.5, 0.75, 1.0, 1.5). For the thermal features, local Nusselt numbers and fin temperature profiles are compared; and for the flow characteristics, velocity profiles, pathlines, and velocity vectors are examined. Finally, average Nusselt number and pressure drop are studied to measure the thermo-hydraulic performance. Despite drops in local Nusselt numbers at some spots on the fin, the average value of relative Nusselt number is always larger than unity, and the degree of augmentation grows with the reducing aspect ratio, while the tube wake region shrinks. The wake-affected fin is significantly benefitted as the relative Nusselt number equals 134.9% at the studied Reynolds number.

For diesel engines, the fuel injection parameters and piston bowl geometry (PBG) significantly influence the working process and exhaust emissions. This paper presents the research results on the effects of the fuel injection parameters such as the diameter of the spray nozzles, injection pressure, the start of injection (SOI), and diameter of fuel particles injected into the cylinder in combination with optimizing PBG on the performance and exhaust emissions of the diesel engine ISUZU 4BD1T. The study procedure was conducted using the specialized simulation software Diesel-RK. The study results showed that the optimization of fuel injection parameters, including reducing the diameter of the spray nozzles, decreasing the fuel jet inclination angle, reducing the SOI, and combined with the proposed PBG, significantly reduces fuel consumption by 2.0 g/kWh, NOx by 10.1%, and soot by 29.5%.

Autonomous mobile robots (AMR) are commonly used in intelligent manufacturing systems. For these robots to operate autonomously in the working environment, in addition to being equipped with a sensor system, algorithms are required to process information collected from the working environment and make control decisions to control the robot's movement in different situations. In this paper, the authors present an algorithm to avoid static, dynamic obstacles and generate local guidance trajectories for the robot to overcome the barriers on its way based on information from the sensor network equipped with the robot. In this, dynamic obstacles are understood as objects moving in the same direction opposite to the direction of the robot or crossing the motion of the robot. The proposed algorithm has been experimentally verified on a differential drive mobile robot combined with a mecanum wheel mobile robot. The results of this research have practical implications for motion control of AMR in industries.

This paper presents the optimization of a CPG-based locomotion controller for a fish robot using Deep Deterministic Policy Gradient (DDPG). Firstly, the rhythm of swimming of an elongated undulating fin-like black Knife fish is generated by Central Pattern Generator (CPG). In the CPG network, the Hopf oscillators are employed to provide the rhythmical output and ensure continuous sinusoidal oscillation even when the CPG parameters are abruptly changed. The smooth transition output of the CPG is dependent on an intrinsic parameter of the oscillator called the convergence speed. This parameter is optimized by a combination of Deep Q-Network (DQN) and Policy Gradient (PG), which overcomes the drawback of traditional DQN, such as providing stable learnings to adapt specifically to dynamic environments. The simulation results demonstrate that the convergence speed of the modified CPG network based on DDPG is improved by about 2.2%. It also indicates that the rhythmical output of the CPG integrated with the DDPG optimizer can provide higher accuracy of oscillatory amplitude (about 1,6%) than do the traditional DQN, leading to high efficiency in controlling the swimming gait of the robotic fish.

This paper describes a study that was carried out to determine the optimum main design parameters for minimizing the gearbox volume of a two-stage helical gearbox. The gear ratio of the first stage, the coefficient of wheel face width of stages 1 and 2, and the allowable contact stress of stages 1 and 2 were all considered carefully in this work to determine their optimum values. A simulation experiment was designed and implemented by a computer program to solve this work. Minitab R19 software was also used to design the experiment and analyze the results. The effect of main design factors on the gearbox volume was analyzed. The optimum value for these parameters was also proposed.

The purpose of this study is to analyze the pavement-friendly performance of an agricultural truck with two types of hydro-pneumatic suspension (HPS) struts on dynamic load coefficient (DLC). The nonlinear dynamical models of two different types of HPS struts with one gas chamber and two oil chambers (Model 1) and with one gas chamber and three oil chambers (Model 2) are set up to calculate their nonlinear vertical forces. A quarter–vehicle mathematical model of an agricultural truck is set up for the analysis of the nonlinear vertical forces of two proposed suspensions which is implemented in MATLAB/Simulink platform. The obtained results indicated that the pavement-friendly performance of Model 2 is better than performance of Model 1. Especially, the values of DLC at axle of vehicle with Model 2 reduce by 6.97% in comparison with Model 1 when vehicle moves on ISO class C road surface at vehicle speed of 40 km/h and full load.

This study proposes a quarter-vehicle dynamic model of a mining dump truck using hydro-pneumatic suspension system (HPSs) suspension system to analyze the ride comfort performance of a mining dump truck under different operating conditions. The root mean square (RMS) acceleration response of vehicle body (awz) according to international standard ISO 2631-1:1997 is selected for performance analysis. The numerical simulation results indicate that awz values increase very quickly under bad operating conditions. The study results are useful reference for designers and manufacturers in the field of off-road vehicle suspension systems.

The current stage in the development of very high frequency (VHF) radio receiving equipment is the widespread introduction of Software-defined radio (SDR) platforms. Such devices allow software control of operating radio frequency parameters of the radio channel, providing both versatility and solutions to the problems of specific radio information systems. The operation of VHF SDR takes place in a complex electromagnetic environment with a lot of in-band and out-of-band interference, and a noticeable level of the radio background, the level of which in industrial areas is several times higher than the intrinsic noise of the radio receiving path. The paper discusses the problems and modern approaches to improve the quality of reception in VHF SDR. In addition, we provide recent developments of VHF SDR in different scenarios and results in some specific applications. The results show promise and practical uses in various fields for communication purposes.

The study introduces the formulation of the radial basis function-based finite element method (RBF-FEM) for bending, free vibration, and buckling analysis of Mindlin-Reissner laminated composite plates by first-order shear deformation theory. The method utilizes the radial basis functions to construct the shape functions from the finite nodes. Compared with the conventional finite element method (FEM), the present RBF-FEM obtains the shape functions with simplicity, especially when the number of element nodes is increasing. The proposed RBF-FEM eight-node element (RBF-FEM-8) is utilized. By applying the Gauss point reduction technique, the method could solve the thick and thin laminated composite plates with high accuracy, quick convergence, reducing mesh size in discretization, and could remove the shear locking phenomenon. Several numerical example studies of the thick and thin Mindlin-Reissner plates with the difference in geometries (including line and curve boundary edges), oriented layers, edge boundary conditions, Young’s modulus ratio, length-to-thickness ratio, are carried out. The results are then compared with other numerical methods and analytical solutions.

The temperature of the brake mechanism greatly affects the braking performance as well as the safety of vehicle movement. In order to evaluate the heat transfer process of drum-brake mechanism, a model of the drum brake mechanism of heavy truck was built by Inventor software. The file of CAD model is then saved as an IGS for import into the CAE environment. The finite element model of the drum was established by Ansys software to analyze the heat of the brake drum during the vehicle braking process. The analysis results show that the temperature distribution on the drum is highly dependent on the braking process. Especially, the values of the highest and lowest temperatures on brake drum are 333 °K and 295 °K when vehicle brakes on a long slope.

The article presents a solution to build a system to identify and detect traffic violations at intersections, applying IoT technology and image processing. The system uses traffic cameras to collect input data for software programs to identify and detect traffic violations on Apps, Websites. The article focuses on building an algorithm to recognize vehicle number plates, detect traffic violations, and warn of collisions of vehicles participating in traffic. Thereby helping managers effectively respond and handle traffic situations in real time.

In order to improve comfort and ride quality of electric vehicle (EV), a modified Skyhook controller is used for controlling the damping coefficient of EV suspension system. A three-degree-of-freedom EV dynamic model is established under two excitation sources such as road surface excitation and in-wheel electric motor (IWM) excitation to evaluate the controller's efficiency. The weighted root-mean-square (r.m.s.) acceleration of the vertical vehicle body ( $${\text{a}}_{{\text{w}}}$$ a w ) according to the international standard ISO 2631–1 (1997) is selected as an objective function. The study results indicate that the design controller for the semi-active EV suspension system has significantly improved the vehicle ride comfort. Especially, the $${\text{a}}_{{\text{w}}}$$ a w value with modified Skyhook controller for semi-active EV suspension system reduces by 15.8% in comparison with passive suspension system when the vehicle moves on ISO class B road surface at vehicle speed of 60 km/h and full load.

In order to evaluate a wheel loader ride comfort using hydraulic isolation system (HIS) of cab with the orifice and the annular orifice, a half-vehicle dynamic model of a wheel loader is established under different driving conditions. Time domain and frequency domain acceleration responses of the vertical driver’s seat and cab pitching angle are selected as the objective functions to analyze and evaluate vehicle ride comfort. The study results show that the amplitude values of the PSD acceleration responses of the vertical driver’s seat with 1.5c0 value of HIS respectively reduce in comparison with 0.5c0 value of HIS at the low frequency region from 2.0 Hz to 20 Hz. Finally, the different operating conditions are investigated and evaluated their effects on vehicle ride comfort with HIS, and the evaluation results indicate that the values of the root mean square (RMS) acceleration responses of the vertical driver’s seat (aws) and cab pitching angle (awphi) change greatly when operating conditions get worse, which means that operating conditions greatly affect vehicle ride comfort.

In this paper, a nonlinear Planar Flexible-Joint Robot system with two degrees of freedom is discussed. Due to the nonlinearities properties and underactuated system, it is essential to design a compatible control scheme. Therefore, a robust control structure relies on the hierarchical sliding mode technique. Using Lyapunov’s theory and Hurwitz's polynomial property, stability of the sliding surface as well as the convergence of the state variable can be ensured. In addition, numerical simulation results using Matlab/Simscape Multibody Link plug-in on Solidworks are also presented and show excellent performance compared to traditional linear controllers. In particular, the results are more obvious when considering the model uncertainty parameter.

This paper presents the results of a multi-criteria decision-making (MCDM) study in cylindrical external grinding SKD11 tool steel. The goal of this research is to find the best input process parameters for dressing process in external grinding to achieve minimal surface roughness (RS) and maximum wheel life (T). First, the EDAS (Evaluation based on Distance from Average Solution) method was used to solve the MCDM problem and the Entropy method was employed to calculate the weights of criteria. Furthermore, an experiment was conducted with six input parameters: fine dressing depth, fine dressing passes, coarse dressing depth, coarse dressing passes, non-feeding dressing, and dressing feed rate. The experiment was also designed using the Taguchi method and an L16 orthogonal array. Based on the results of the work, the best dressing mode for external cylindrical grinding has been proposed.

The objective of this paper is to illustrate an alternative control algorithm for power converters which have the task of introducing the energy generated by systems based on the use of renewable sources such as, photovoltaic or wind power, in to small-sized networks, microgrids. Virtual Synchronous Generator can operate both in parallel to the main network as well as in isolated and autonomous conditions (islanding-mode). The contribute of this work is to drive a consolidate approach, made in time domain, in a more flexible and less time-consuming approach based on Park transformation.

Cab’s suspension system plays an important role to improve vehicle ride comfort. Therefore, a half-vehicle dynamic model of an agricultural tractor is established to analyze the effect of the design parameters of cab’s suspension system on an agricultural tractor vehicle ride comfort. The stiffness and damping coefficients are analyzed respectively based on ISO 2631-1997 standard which defines methods for the measurement of periodic, random and transient whole-body vibration. The analysis results show that the stiffness and damping coefficients of cab’s suspension system has a great effect on vehicle ride. In addition, the values of the stiffness and damping coefficients are respectively evaluated to affect vehicle ride comfort.

Machining CFRP composite normally has two issues concerned, including minimizing machining defects which strongly influence on working ability during the services and reducing particle dust emitted in the air which is inhaled by operators. This article presents a study of investigating the effect of tool geometry or a number of cutting edges engaged on the surface integrity of trimming CFRP composites. Three carbide tool geometries, namely 2 helix flutes, 3 helix flutes, and 4 helix flutes, are selected for the experimental study. The surface integrity given by each cutting tool is qualitatively evaluated by the scanning electron microscope technique. The results show that when machining length is still small, 4HF tools exhibit the better machining quality compared with those given by other tool geometries. However, when machining reaches longer, it is observed that due to the stick of microchip in the grooves between two consecutive cutting edges, 4HF tools generate worse machining quality, characterized by matrix smearing and holes across machined surface, than those given by 2HF and 3HF tools. The result of the current study can be concerned as a guidance for selecting tool geometries for getting better surface integrity of trimming CFRP composites.

This article presents a multi-objective optimization process of surface grinding for Aluminum alloy 6061 in CNC machine tools. The aim is to find the optimal set of grinding parameters that can simultaneously satisfy maximizing material removal speed (MRS) and minimizing surface roughness. The partial factor method 24–1 is used to determine the number of tests. Four process parameters are chosen as input parameters, namely spindle speed (Rpm), feed rate (Fe), depth of cut (aed), down feed (Df). The multi-objective function optimization becomes only the optimization of Composite Desirability function (CDF). Regression functions to predict both surface roughness and material removal rate are constructed based on the experimental results. The results reveal that when CDF reaches the value of 0.669, it can be found the minimum surface roughness of 0.19 µm and MRS reaches a maximum value of 16.23 (g/h).

The tractor semi-trailer often causes accidents when braking. In this paper, the author uses the multi-body system (MBS) method and the Newton-Euler method to establish a system of vehicle dynamics equations. Matlab-Simulink software is used to survey the braking efficiency of vehicles on a straight road with road surface profiles according to ISO 8608–2016. When a tractor semi-trailer is run straight at 80 km/h on road surface profiles A, B, and C, the slip ratio of wheels is less than 10%; the braking acceleration of the vehicle is 6.2 m/s2, meeting the requirements of ECE-R13 standard [1]. If the tractor semi-trailer is run on road surface profiles D, E, and F, the braking force value is reduced by about 23 ÷ 44%; the slip ratio of the middle and rear axle wheels reaches 100%; the braking acceleration of the vehicle is less than 5.8 m/s2, which does not meet the requirements of ECE-R13 standard [1].

This paper presents a design method for a compound non-circular gear train (CNCG) with a pair of internal gears and mathematical model synthesis of the mating centrode for the CNCG train according to the mating centrode of gear 1 and gear 4. A CNCG train design with a variable speed and torque range from 0.4 to 1.8, after evaluating and discussing the kinematic characteristics of the CNCG train with the criterion is that the mating centrode of the non-circular gears in the CNCG train is convex curves. In the CNCG train, the outer ring gears are shaped by the rack cutter, while the shaper cutter shapes the inner ring gear.

This paper reports the results of an optimization study on the effect of major design factors on the length of a two-stage helical gearbox. Five major design factors were investigated in the study including the first stage gear ratio, the coefficient of wheel face width of stages 1 and 2, and the allowable contact stress of stages 1 and 2. A simulation experiment was also designed and accomplished by a computer program. Furthermore, Minitab R19 software was applied to analyze the experimental results. The impact of key design factors on gearbox length was investigated. The optimum values of the parameters to obtain the smallest gearbox length were also proposed.

This paper introduces the results of experimental research on process Gas Metal Arc Welding SS 400 carbon steel thick plates 50 mm with narrow gaps and small chamfer angles using welding equipment PLEXTEC 500X of LINCOLN corporation (USA) in an industrial production scale in Vietnam. The quality of SS 400 carbon steel welded plates was evaluated at three levels as 25%, 50% and 75% of the weld height in combination with the result of measuring microstructural characteristics in different specific zones: base metal; head-affected zone (HAZ), the boundary between the weld metal and the HAZ such as the weld center zone.

The article introduces some experimental research results on the application of plasma welding technology for SUS 304 stainless steel thin plates, using welding equipment of LINCOLN CB-MATIC SF 32–33 (USA) with a production industry scale in local conditions of Vietnam. The quality of the weld is preliminarily assessed through the criteria of its surface morphology and the maximum deformation of the weld structure in the state after natural environmental cooling. The experimental results help to set the limitation of the domain of in-depth investigation on the influence of key technological parameters on the mechanical properties and microscopic structure of the weld material, using an experimental design method as a scientific platform to determine the welding mode in accordance with the technical requirements of the mechanical product, which needs to be manufactured.

This paper presents the design of an adaptive tracking controller based on the RBF neural network to control the trajectory tracking of a three-wheeled omnidirectional mobile robot (TWOMR) taking into account the uncertainty nonlinear factor. When the robot moves, it will be affected by some uncertain components of the model, unknown noises, the interaction of parameters in the robot system. The Radial Basis Function (RBF) neural network is used here to estimate the uncertain components and unknown noises of the robotic system. The adaptive traction controller is proven stable through the Lyapunov benchmark. The effectiveness of the controller is verified by simulation results on Matlab software – Simulink.

Recently, there has been an active growth in the number of electrified vehicles. At the end of 2021, the number of electric vehicles was 16.5 million, three times more than in 2018. To increase competitiveness, manufacturers of electric vehicles increase plants’ power and battery capacity. This leads to an increase in the release of heat into the cooling system. This article discusses the main directions for improving the temperature control systems of electrified vehicles. A literature review is carried out, problems that have not been studied before are noted, and possible ways to solve them are presented. The influence of the organization of the airflow in the air path of the cooling system on the aerodynamic resistance is considered. A solution for the operation of electric vehicles under conditions of extreme ambient temperatures for the battery, both positive and negative, is proposed. The use of an immersion thermal control system on vehicles is analyzed.

Aluminium use has expanded recently due to its excellent strength-to-weight ratio and strong erosive and corrosive resistance. The use of aluminium matrix composites has grown in various industries, such as aerospace, automobiles, ships, and spacecraft. This paper selected Aluminium 6061 for matrix and silicon carbide for reinforcement for better mechanical properties. Aluminium metal matrix composite (Al-MMC) was manufactured by the stir casting method. Cow dung ash and buffalo dung ash of 150 µm was prepared and added as reinforcement to decrease the density of the composite. Pin on disc tribological tests was performed by changing the load from 10 to 40 N with a 10 N step. The wear rate of the composite was observed at different loading conditions. Microstructural characterization of worn surfaces was analyzed using optical and scanning electron microscopes. It was used to observe microstructure, reinforcing particle size, shape, and dispersion in the composite to determine the physical qualities.

In the original version of the book, the following belated corrections have been incorporated: The author name “Muthuramalingam Thangaraj” has been changed to “Thangaraj Muthumaralingam” in the Frontmatter, Backmatter and in Chapter 36. The book has been updated with the change.