Advances in Control, Signal Processing and Energy Systems

Assuming that many physical models can be decoupled, an anti-windup control scheme for nonlinear cascade systems is proposed. Taking into account that saturation appears frequently, in order to overcome this difficulty, an efficient control approach is developed. The paper is divided into two parts; First, the design of a cascade control system with dynamic controllers in the inner and outer loops, considering the closed-loop stability in the controller design with a suitable anti-windup compensator; Secondly, a PID cascade controller design in the inner and outer loop is presented, when the parameter tuning in both control schemes is done by particle swarm optimization (PSO). However, in this case, the implementation of an anti-windup compensator is not needed. Apart from the theoretical background, two numerical examples are shown to corroborate the provided results.

In this paper, we develop an estimation model for carbon monoxide (CO) air pollution concentrations. CO is an important pollutant which is used to calculate an air quality index (AQI). AQI becomes less reliable as the proportion of data missing due to equipment failure and periods of calibration increases. This paper presents the Unscented Kalman filter (UKF) to predict missing data of atmospheric carbon monoxide concentrations using the time series data of monitoring stations.

The paper presents a technique to determine the optimal model order of an electrochemical system with the help of system identification. The study has been performed for the case of different tea samples on a voltammetric electronic tongue. The transfer function model of the system with different combinations of number of poles and zeros are identified using the response data obtained from the electronic tongue. Based upon the normalized root mean square (NRMSE) criteria, the model fit for different model orders are compared and the optimal order of the system is determined.

This paper describes the analysis of the IEC61850 MMS and GOOSE communication network using a laboratory setup. The MMS communication between the OPC server and simulated IED is established and communication is captured using the open-source tool Wireshark. The normal flow of communication is analyzed and decoded first and IEC61850 data is manipulated in IED to determine how the communication flow deviates from the standard flow of communication. Reporting to the Station HMI and SCADA is done using MMS communication service on the Ethernet network. To determine the status and quality of the IEC61850 data exchanged between IED’s (GOOSE), IED and HMI (MMS), Wireshark is used to capture the network traffic between these two scenarios. Moreover, these captured scenarios in Wireshark are used to diagnose whether the error is a configuration error or the network error. These Wireshark log files are sent by the users of the IED’s in the substation to the vendors of IED to diagnose the error codes. The efforts in diagnosing the errors can be reduced if one knows the flow in the normal scenario and abnormal scenarios which can help to reduce the time to troubleshoot the IEC61850 communication network.

As per researchers, “AI research” is defined as the study of intelligent agents, where an intelligent agent is any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Through this paper, we are proposing IntelliNet, which is an Intelligence Delivery Network (IDN). The objective of such a network is to infect intelligence into all the objects or devices which will be connected with the network. The prime reason behind infecting intelligence and not injecting it into any object is that here the source intelligence system not only delivers intelligence to the object but also senses all types of possible events for gathering knowledge in order to infect other objects as well, thereby making ordinary devices smart and intelligent.

Text mining is the process of extracting and/or deriving high-quality information from unstructured text by properly structuring the raw text. The structured texts serve as ideal candidates for revealing the syntactic and semantic interpretations encapsulated in them. To do so, we need to employ different methods of text mining and text analytics. Text Analytics deals with the objective of evaluating and assessing text by the application of natural language processing and other linguistic-oriented analytical methods. Text-based sentiment analysis aims to determine the attitude and sentimental state of an author by analysing different tokens of the texts in terms of their polarity. The aim of this paper is to propose a hybrid Lexicon-based sentiment and behaviour prediction system which can help one to comprehend the sentimental as well as the behavioural context of the author. We have used two sets of lexicons, viz. SenticNet 4.0 Lexicon and our own manually created Profile Lexicon in order to assess the input text and to predict the sentiment conveyed by the text as well as to identify the behaviour of the author. Our system works fairly in case of predicting both sentiment and behaviour by offering an accuracy of approximately 90%. Such a system has immense potential in identifying the real intention of an author once the behavioural and sentimental patterns of an author are predicted consummately.

Effective object detection must be able to handle cluttered visions which convert into the object size, location, orientation, and other movements. We presumed that Computer Vision System Toolbox™ MathWorks offers a variety of techniques for handling challenges in object detection. In this paper, we elaborate on how to detect an object in a cluttered scene, given a reference image of the object. The output of this paper explains an algorithm for detecting a recognized object depending on finding the vision points correspondences between reference and target images. It can detect each and every object in spite of a scale change or in-plane rotation and quite extend to robust with small amounts of out-of-plane rotation. This method of object detection through recognized feature points works best for objects that exhibit non-repeating texture patterns, which give rise to unique feature matches. In connection with this, present algorithm is designed for detecting a specific static object only.

This work presents a new idea for human behavior recognition based on dictionary learning algorithm and collaborative representation-based classification approach. In this paper, we have proposed an l₁ – l_s-based KSVD algorithm for learning a dictionary and collaborative representation is used in the classification phase for this problem. The performance of our proposed idea for human behavior recognition problem establishes the superiority of our new idea.

Breast cancer has become one of the major types of cancer-caused deaths among women of different countries throughout the world. One of the major problems of this type of cancer disease are quick detection or identifying of disease in early stages. In the cases of technologically lagging countries mortality rates are very high due to lack of early diagnosis technology of disease. According to the opinion of different clinical experts, today mammography is one of the most effective diagnosis technologies in medical science domain. So there is a requirement for more accurate methods which can easily diagnose any type of abnormalities in women breast without any kind of human intervention with higher accuracy rates. Segmentation is an approach that is very much required to identify the unambiguous region from the mammogram image. Intensity, texture, and shapes are extracted from the segmented mammogram image. The role of image processing is to detect cancer in human body when input data is in the form of images. For mammogram image classification, the feature extraction of an image with statistical parameter measurement is very important approach. Different types of feature extraction methods are generally used for better classification of abnormality present in mammogram. This technique will provide higher accuracy rates at a comparative higher speed. The statistical parameter includes entropy, mean, regression, correlation, skew, standard deviation. The experimental results achieved 89% accuracy, 74% specificity, and 89% sensitivity, illustrating the usefulness of the technique for identifying and classifying the cancer in mammogram images with maintaining more accuracy.

Voltage instability in power system is becoming more and more important because of the regular growth of power system and lack of efficiency in reactive power management. The voltage instability of a power system is associated with a voltage drop. Voltage drop has a cumulative effect unless efficient reactive power sources are available for voltage regulation. In this paper, the voltage stability region of IEEE standard bus systems is visualized using P-Q curve technique. Voltage stability margins are also visualized using local measurement techniques. Then, the change in stability margin is observed by introducing FACTS and DG. Optimum location of installation of these devices is determined.

In recent year, Light-Emitting Diodes (LEDs) have been widely used due to their excellent advantages over conventional light sources, e.g., like incandescent lamps, gas discharge lamps, etc., with their high efficacy, low power consumption, and long lifetime. Reliability and long lifetime will determine the economical and ecological success of LED in lighting systems. LED systems can in general reach very long lifetime of up to 200,000 h with appropriate designed. For solid state, LEDs, the light output, efficiency, spectral distribution and lifetime is strongly dependent on operating temperature. In this study, the thermal tests under ambient temperature have been performed. The temperature build up at the substrate area and sink area has been measured by the Thermal IR imager at every 5 min interval. Two processes have been adopted. Initially the measurement of temperature was done and recorded when the LEDs are connected with constant 300 mA driver and another is when LEDs are connected with rated DC power supply, i.e., without driver condition. To find the extra heat generation using driver or not. But the temperature generation is nearly same for both the conditions, however details experimental results has been furnished and analyzed herein after.

The present work deals with performance study and stability analysis of an LED driver system. An LED driver based on buck-boost topology is designed and simulated in MATLAB Simulink environment. The driver satisfactorily operates LED modules having power rating in the range of 6 W to 24 W. The power factor and Total Harmonic Distortion comply with standard recommended values. The mathematical model of the LED driver is formulated and the stability analysis of the designed driver is carried out during its operation.

In this paper, we describe the instrumentation setup for wireless condition monitoring of induction machine in a laboratory environment. Four parameters, viz., stator voltage, current, body temperature, and rotor speed were sensed and fed to a dedicated hardware unit (DHU). This DHU was operated using commands from a desktop computer, acting as an operator station. An Arduino Uno board was used as the data collection unit of the DHU and interfacing to the ZigBee module. Data packets with all four sensed parameters of 5 s duration was continuously collected and transferred to the operator station for real-line display in a graphical user interface. All parameters had less than 1% error in their measurements.

Present circumstances lead a major challenge to the non-renewable sources of energy, causing more need of renewable energy. The common characteristics of renewable energy except for hydroelectricity are low energy density and high resource dispersion. Moreover, wind, solar, and ocean energies are stochastic and intermittent resources but solar energy is available in an ample amount almost in every strata of the world and is an effective renewable source of energy. Here we develop a prototype of large-scale system for feeding local domestic loads with solar energy and to store the energy for using, during peak hours when our traditional energy sources are not able to satisfy the demand of energy needed by the domestic loads. In our small scale approach at laboratory environment, instead of using solar photo-voltaic module, we used solar photovoltaic simulator as source to generate electricity. The source voltage is then converted by using a DC–DC buck type converter to a required value for charging a 12 V lead-acid battery which is used as an energy storage element. Here we implemented the Maximum Power Point Tracking algorithm of perturb and observe technique to extract maximum power and to transfer the extracted energy to our desired storage element by developing a program which is interfaced with hardware using Arduino Uno.

This paper deals with the comparative study on daylight availability on horizontal working plane of a simulated room under identified CIE (International Commission on Illumination) Standard skies prevailing in Roorkee, India for the three seasonal conditions, viz. equinox, summer, and winter solstices. Daylight coefficient method (DC) and finite element method (FEM) have been applied to develop computer programs in MATLAB environment for this simulation. Here daylight availability is predicted for a room with single-sided window of opening areas 20% of floor area and sill height 1 m from floor with eight cardinal window orientations. Analysis revealed that during summer the amount of daylight availability is maximum as the sun shines directly on the Northern Hemisphere during summer. Polar axis of earth is tilted 23.5° to the orbital plane. Differential and changing illumination pattern on earth for different seasons is due to combinations of rotation, revolution, and tilt of polar axis.

Present day civilization faces a never-ending growth for the demand of electricity. This necessitates an increase in the number of power stations and their capacities and consequent increase in the power transmission network connecting the generating station to load centers. Depending upon the load demand, the electrical generators operate under various generating conditions. The generating costs of different power plants are also different. So it is very much important to operate the power plant at optimal generation with minimum cost condition. In this paper, an attempt has been made in minimizing the cost function and the transmission line losses utilizing Modified Harmony Memory Search (MHMS), and Differential Evolution (DE) optimization techniques for a three-unit system under known maximum and minimum operating region of each generating station.

This paper proposes and examines a sinusoidal pulse width modulation (SPWM)-based single-phase diode clamped multilevel inverter for generation of multilevel output voltage. The SPWM signals and digital square pulses are generated using a single PWM module and I/O port of a PIC microcontroller. The performance of the proposed method is checked through simulation after the design of a diode clamp multilevel inverter for 3-level, 5-level, and 9-level output voltage. The 5-level and 3-level output have also been produced by hardware implementation of the designed circuit. Total harmonic distortion (THD) for 3-level, 5-level, and 9-level output voltage waveforms are analyzed.