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Über dieses Buch

This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems.

The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.

Inhaltsverzeichnis

Frontmatter

Tracking Control for Unknown Nonlinear System Based on Augmented Matrix Algorithm

Abstract
Based on the augmented matrix and approximate dynamic programming algorithms, the \(H\infty \) tracking control problem for unknown nonlinear system is addressed in this paper. An identifier NN is first used to approximate the unknown system. An augmented matrix based on the desired trajectory and system state is then constructed using the identifier, such that the tracking control problem is transformed into the regulation one. We use another NN to approximate the performance index function of the HJI equation, such that \(H\infty \) tracking control pairs are calculated without solving the HJI equation. Moreover, we use an estimation algorithm to estimate unknown parameters in neural network. Finally, a simulation is presented to demonstrate the validity of the proposed method.
Yongfeng Lv, Xuemei Ren, Linwei Li, Jing Na

A PSO-Based Integer Programming Solution to Impulsive-Correction Projectile Systems

Abstract
This paper presents a novel integer programming approach for the design of a class of impulsive-correction projectile systems with discrete, flexible-time interval and finite-energy control. In terms of its impulsive characteristics, the task is described as the formulation of minimizing the working number of impulses and minimum control error (i.e., miss distance) with integer design variables. In order to solve such integer programming problem, particle swarm optimization (PSO) mechanism is employed to find optimal setting of impulsive control. A modification of the basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. Meanwhile, a rounding function operation is applied to the modified PSO considering the constraints of integer design variables. Additionally, an efficient way to design the dimension of the search space is investigated to acquire both satisfactory precision and less iterative number. Finally, simulations with nonlinear dynamics are conducted to validate the PSO-based integer programming algorithm by comparing with conventional optimization methods. It is illustrated that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately.
Ruisheng Sun, Zhigang Yang, Qiao Hong

Gas Plume Tracking of Micro-aerial Vehicle in Tunnel Environment

Abstract
This paper deals with the problem of gas plume tracking by designing and analyzing a system of gas detection and ultrasonic perception for an unmanned aerial vehicle (UAV) in tunnel of GPS-denied environment. Plume concentration information and distance information to wall detected by the system are used to predict a probable direction of drone to next station. Specifically, the idea of integration of gas tracking and three-dimensional (3D) wall-following is introduced to give a probable direction of next spot in terms of the perception system. Moreover, the framework and dynamic modeling of aerial flight system are built according to attitude information of UAV. Then, three types of algorithms are described: first is zigzag to find gas plume, the second is concentration gradient algorithm in tracking odor, and the last one is three-dimensional wall-following navigation method. Finally, the performance capabilities of the flight strategy of integration are validated through real-world experiments in tunnel.
Qiuyue Yu, Lei Cheng, Xin Wang, Chuang Shang, Rui Peng, Quanmin Zhu

A Review of Current Condition Monitoring and Fault Diagnosis Methods for Slewing Bearings

Abstract
Low-speed and heavy-load slewing bearings are applied broadly for major mechanical equipment. Compared with ordinary bearings, large slewing bearings have complex structures and work in variable environments. In order to increase productivity, reduce maintenance costs, and ensure the safety of people and equipment, it is of great importance to monitor and diagnose faults in real time. This paper aims at providing a state-of-the-art review on methods for condition monitoring and fault diagnosis of low-speed and heavy-load slewing bearings. Finally, the current needs and challenges are presented to provide a reference for future research.
Fengtao Wang, Chenxi Liu

Research on Torque Optimization Allocation Strategy About Multi-wheel Vehicles

Abstract
Multi-wheel vehicles are extensively used in military, agricultural machinery, and construction machinery. Since multi-wheel vehicle is one type of over-actuated systems, it is required that the kinematics and dynamics of all wheels have to be coordinately controlled. Therefore, the coordinated wheel torque control is the key factor. In this paper, the torque optimization allocation strategy of multi-wheel skid steering vehicle with independent in-wheel motors has been studied based on its dynamic model. The dynamic rule based on wheel torque distribution method has been studied in this paper, as well as optimal torque allocation method based on control allocation. Weighting control allocation error and control energy as the optimization target, wheel torque control allocation problem can be solved mathematically using quadratic programming method. Integrating with wheel slip control and actuator fault redundancy control schemes, the optimization algorithm is correspondingly designed, which improved the dynamic performance and safety of steering vehicle. The effectiveness of wheel torque distribution strategy was validated using Matlab/Simulink software and the simulation platform of the multi-wheel vehicle, and the simulation results show that the wheel torque, when a wheel motor fails, can be redistributed among the effective motors.
Hongjie Liang, Yue Ma, Yu Wang, Jinning Zhi, Yi Li, Yifan Peng

The Application of Data-Level Fusion Algorithm Based on Adaptive-Weighted and Support Degree in Intelligent Household Greenhouse

Abstract
The paper first details the general structure and functions realization of intelligent home greenhouse control system. In order to make the data obtained from the intelligent home greenhouse system in this paper more accurate, the paper mainly explores how to accurately perceive the environment. Aiming at the error of same type sensors’ data in household greenhouse environment, data-level fusion is used to reduce the error and obtain more accurate value of same type sensors’ data. In order to improve the precision and reliability of data-level fusion, a weighting-coefficient construction method based on support degree and adaptive-weighted is proposed, which not only ensures the reliability of data fusion but also makes the fusion result more stable. The accuracy of data fusion directly determines the precision and quality of greenhouse intelligent control. The experimental results show that the fusion result adopting the proposed method of this paper is superior to the result of traditional average-estimation fusion and data fusion based on support degree.
Chang-tao Wang, Zhe Wang, Yi Zhu, Zhong-hua Han

Parameter Estimation for Control of Hammerstein Systems with Dead-Zone Nonlinearity

Abstract
This paper focuses on the parameter identification and control for Hammerstein systems with dead-zone nonlinearity by using piecewise linear parametric expression method and model predictive control approach (MPC). To linearize the dead-zone nonlinearity, the piecewise linear functions are exploited to deal with dead-zone, and then, a piecewise linear parametric expression (for short, PLPE) algorithm is applied to describe the dead-zone function. Based on the described function, the considered system is transformed to a classical regression form. The parameters of the Hammerstein systems with dead-zone can be easily estimated by using least squares method. Based on dead-zone compensation, an MPC method is introduced to achieve the signal tracking output. Numerical simulation results indicate that the control system not only achieves the tracking output of the reference signal with a small tracking error but also produces an outstanding output response.
Linwei Li, Xuemei Ren, Yongfeng Lv

An Improved Online Denoising Algorithm Based on the Adaptive Noise Covariance

Abstract
Dealing with noisy time series is an important task in many data-driven real-time applications. In order to improve the veracity of the measured time series data, an effective denoising method is of great significance. For some applications with online requirement, the measurement would need to be processed to get rid of noise as soon as it is obtained. In this paper, a novel method was proposed to process relatively smooth time series data with annoying complex noise based on a second-order adaptive statistics model (SASM). However, in practical process, the nonzero mean measurement noise covariance “R” was unknown, and unfortunately it usually has a huge impact on the denoising effect. Therefore, this paper proposed a self-adjustment algorithm for measurement variance searching, by means of introducing a forgetting factor to estimate “R”. In this way, “R” would be convergent to the real value reasonably fast. The effectiveness of the method was verified by the simulation experiment. The results show that the proposed method can not only make “R” to be convergent to real value but also achieve the favorable denoising effect.
Tingli Su, Shenglun Yi, Xuebo Jin, Jianlei Kong

Hopfield Neural Network Identification and Adaptive Control for Bouc–Wen Hysteresis System

Abstract
An adaptive controller is proposed for hysteresis nonlinear systems where the coefficients were estimated by Hopfield Neural Network (HNN). First, a Bouc–Wen model is applied to describe the hysteresis nonlinearity. Then, a nonlinear system model is employed with the unknown parameters of the state-space equation and a new HNN is designed to identify the coefficients. Finally, an adaptive controller is proposed and the stability is guaranteed by a Lyapunov function candidate. Simulation results verify the effectiveness of the proposed identification and adaptive control approach.
Gao Xuehui, Sun Bo, Zhang Chengyuan

Harmonics Elimination in Permanent Magnet Synchronous Generator with Current Injection at DC Side

Abstract
The large number of harmonics in permanent magnet synchronous generator (PMSG) stator current is harmful to wind turbine generators (WTGs), which will greatly increase current ripple and torque pulsation, and finally reduce the generator efficiency, especially in modern high power wind generation occasion, representing challenges. In this chapter, the low harmonic multi-pulse rectifiers with current injection at DC side are presented, in order to improve the low power factor (PF) of uncontrollable rectifier and overcome the high failure ratio of pulse width modulation (PWM) rectifier. The proposed strategy is to use the direct current injection at DC side in PMSG to compensate the current harmonic, which brings about less harmonic of generator stator current. Simulation results show the correctness of the theoretical analysis and feasibility of the proposed power converter and compensation strategy.
Xiao-qiang Chen, Shou-wang Zhao, Ying Wang, Min Li

Establishment of Creep Model of Non-asbestos Sealing Composite Material by Beater-addition Process and the Creep Performance Research

Abstract
Creep resistance is one of the important properties of the sealing material, which is the main factor affecting the life of the gasket. There are many factors influencing on the creep properties due to the fact that non-asbestos gasket materials are a kind of composite material of multiple components. The theoretical research, experimental study, and the establishment of mathematical model of the creep are the popular field. In this paper, based on non-asbestos gasket materials, the creep constitutive equation of non-asbestos gasket materials at constant temperature under constant load condition was established, and the creep properties was tested and fitted, through the combination of three parts: the Maxwell model in series connection with two V-K models in parallel, It is shown from the results that the creep model can be used to reflect the creep characteristics of the material. The obtained creep curve shows that the creep of the gasket mainly occurs in the initial 10 h. With the increase of stress, the initial deformation of the gasket increases, and the deformation of the gasket increase with the increase of time. At the same time, the creep variable fitting shows a relatively well log curve characteristic, so the creep data can be fitted by the log curve.
Meihong Liu, Yuxian Li, Yongfa Tan

Position Estimation for Planar Mechanical Systems via McDE-PF Based Sensor Fusion

Abstract
To estimate the position of planar mechanical systems (PMS),a novel sensor fusion approach based on distributed particle filter (PF) is presented to fuse the measurements from an accelerometer and the motor encoders. As the local filter, the PF is improved both by adopting an optimized proposal distribution and by choosing the memetic compact differential evolution (McDE) resampling. Comparative experimental studies confirm the validity of the proposed fusion method.
Guangyue Xue, Jing Guo, Jingkai Wang, Qiang Chen

U-Based Sliding Mode Controller Design and Application for Nonlinear Systems

Abstract
This article considers sliding mode control of a class of non-affine nonlinear discrete systems. The sliding mode controller has been designed to force the states of the nonlinear system into prescribed sliding surface and U-model control to solve non-affine controller problem. The non-affine term existed in the form of polynomial equation based on Taylor series expansion theory, and is obtained by resolving a polynomial equation. The industry process is provided to show the application of the sliding mode control method. A simulation result is provided to illustrate the feasibility and effectiveness of the proposed scheme.
Yang Li, Qiong Wu, Jianhua Zhang

Dynamic Modeling and Modal Analysis of RV Reducer

Abstract
RV reducer is an important component of the joint arm in the industrial robots, and the dynamical characteristics are essential in these system designs. Many research have been done toward the static mechanics and vibration analysis for the robot joint arm to improve the positioning accuracy. Considering the influence of system stiffness on vibration characteristics, this paper first builds a dynamic model of a RV320E reducer, which is based on the lumped parameter method. The natural frequency of the system is then obtained by solving the free-vibration equation. The vibration mode of the first eight natural frequencies is summed up by using the induction method. The paper provides specific theoretical basis for the design and application of RV reducer.
Li-rong Wu, Zheng-ming Xiao, Heng Zhang

Adaptive Parameter Identification and Control for Servo System with Input Saturation

Abstract
In this paper, an adaptive online parameter identification law is investigated by the extracted parameter error information for the position servo system, and the improved exponential reaching law is employed to design the controller to enhance the tracking performance. The chattering problem is weakened using the proposed method. Moreover, several adaptive parameters are adopted to suppress the effect of saturation when the limited input affects the system tracking performance. Finally, simulations are conducted to verify the effectiveness of the proposed method.
Liang Tao, Qiang Chen, Yikun Luo, Yurong Nan

Decentralized Adaptive Synchronization of a Class of Discrete-Time Coupled Hidden Leader–Follower Multi-agent Systems

Abstract
In this paper, the challenging problem of decentralized adaptive control for a class of coupled hidden leader–follower multi-agent systems is studied. Each agent is described by a nonlinearly parameterized uncertain model in discrete time and can receive the history information from its own neighbors. The leader agent knows the desired reference trajectory, while other agents have no access to the desired reference signal. In order to tackle unknown internal parameters and unknown high-frequency gains, a projection-type parameter estimation algorithm is presented. Using the certainty equivalence principle and neighborhood history information, the decentralized adaptive control is designed, under which the boundedness of identification error is guaranteed with the help of the Lyapunov theory. Under some conditions, the whole multi-agent system eventually achieves strong synchronization in the presence of strong couplings. A simulation example is given to support the results of the proposed scheme based on the projection-type parameter estimation algorithm. Finally, we conduct the simulations using the combination of projection and one-step-guess method, which can also achieve the strong synchronization of the whole system.
Xinghong Zhang, Hongbin Ma, Nannan Li, Chenguang Yang, Mei Wu

Improved NSGA-II Algorithm for Multi-objective Scheduling Problem in Hybrid Flow Shop

Abstract
In this paper, multi-objective optimization for hybrid flow shop scheduling problem is investigated. The delivery time penalty and the load imbalance penalty are taken as the evaluation metrics. We describe the optimization framework for this hybrid flow shop problem and design an improved NSGA-II algorithm for solution searching. Specifically, a multi-objective dynamic adaptive differential evolution algorithm (MODADE) is proposed to enhance the searching efficiency of the basic differential evolution operations. MODADE calculates the similarity between different individuals based on their Hamming distance, and dynamically generates the high-similarity individuals for the population. We further improve the MODADE algorithm by integrating the AP clustering mechanism. We compare the proposed algorithm and compare it with the state-of-the-art solutions. The numerical result shows that the proposed MODADE algorithm outperforms others in terms of the algorithm convergence, the number, and distribution of Pareto solutions.
Zhonghua Han, Shiyao Wang, Xiaoting Dong, Xiaofu Ma

NSQGA-Based Optimization of Traffic Signal in Isolated Intersection with Multiple Objectives

Abstract
In this chapter, a novel multi-objective optimization algorithm is investigated to deal with the issue of signal timing in an isolated traffic intersection aiming at releasing traffic congestion, reducing travel delay, maximizing the traffic flow, and minimizing pollution. The throughput maximum, stop times, and delay time of motorized traffic and non-motorized traffic are selected as the objectives of the optimization problem, and quantum computing is integrated with the genetic algorithm to obtain optimized traffic signal timing plan to upgrade the performance of intersection with faster convergence and higher accuracy. A numerical simulation study is conducted on MATLAB in this research work as a case study with a Non-dominated Sorting Quantum Genetic Algorithm (NSQGA), and the simulation results show that the proposed NSQGA algorithm performed superior to the conventional NSGA-II algorithm in effectively coordinating the traffic signal timing plan for an isolated intersection to improve the traffic capacity, efficiency, and safety of traffic system.
Feng Qiao, Haochen Sun, Zhaoyan Wang, Fashakin Alexander Tobi

Multimode Processes Monitoring Using Global–Local MIC-PCA-SVDD

Abstract
A multimode processes monitoring method using global–local MIC-PCA-SVDD is presented. Our method contains the procedures of mode division stage, offline modelling stage and online monitoring stage. At mode division stage, mode division using spectral clustering and multimode processes continuous characteristic is developed. It can divide multimode processes into multiple modes without priori multimode information. At offline modelling stage, considering multimode, global similarity and local non-similarity characteristics, global–local MIC-PCA-SVDD constructs multiple local models and a global model for monitoring. Our method considers dissimilarity between different modes and similarity in multimode processes. At online monitoring stage, different radiuses and distances between testing samples and the centre of the spheres using SVDD models are obtained for multimode processes monitoring. The advantages of SVDD in dealing with non-Gaussian and nonlinear data are used in our method. SVDD has no distribution assumption in which multimode processes data can be mapped to the high-dimensional feature space to construct multiple hyperspheres for global and local monitoring. The experiments of the penicillin fermentation processes are used to validate the feasibility and availability.
Shuai Li, Xiaofeng Zhou, Haibo Shi, Zhongwei Wang

Multi-switching Master–Slave Synchronization of Non-identical Chaotic Systems

Abstract
This paper investigates the multi-switching master–slave synchronization of non-identical chaotic systems in which state variables of a master system are synchronized with different state variables of a slave system using the sliding mode control technique. To design the appropriate controllers via sliding mode control for different switches, Lyapunov stability theory is taken into account. Theoretical results are applied by considering two non-identical chaotic systems where one is considered as master system and another is considered as slave system. Numerical simulations are performed to justify the theoretical results discussed.
Shikha Singh, Ahmad Taher Azar, Quanmin Zhu

Improving Transient Performance of Modified Model Reference Adaptive Control

Abstract
This paper provides a novel method to improve the transient performance of the model reference adaptive control (MRAC) system. In this proposed framework, a new compensator constructed using the known dynamics is employed to reshape the reference model. Then to retain the closed-loop system stability, a modified adaptive law is provided to diminish the disparity between the modified reference model and the original reference model. Through this modification, the norm bound of the tracking error can be reduced via rigorous theoretical analysis. A wing-rock aircraft is used as the simulation example to verify the effectiveness of the proposed control strategy. It is shown in simulations that the high-frequency components in the tracking error and control signals can be diminished, and the improved transient response of the proposed control can be achieved in comparison to the standard MRAC.
Jun Yang, Yafei Liu, Jing Na, Guanbin Gao

A Simulation Study of PEMFC Flow Channels Using a New Hybrid Method

Abstract
Among the number of fuel cells in existence, the proton-exchange membrane fuel cell (PEMFC) has been favoured because of its numerous applications. Computational fluid dynamics (CFD) plays an important role in the development by providing in-depth analysis of PEMFCs gained from studying fluid flow and heat and mass transfer phenomena. The output obtained is useful for reducing the need for expensive prototypes and cutting down test time by a substantial amount. This study is aimed at investigating the advances made in the use of CFD as a technique for the optimization of PEMFCs and studying the effect of some parameters on the performance of the fuel cell (FC) model, by using a new hybrid approach of CFD and Simultaneous Hybrid Exploration that is Robust, Progressive and Adaptive (SHERPA) to study, evaluate and improve the performance. Observations from the CFD results showed that a serpentine-type channel with curved bends would be required for efficient water removal. While further optimization of the model in HEEDS recommended the channel be modified to a 1 × 1 channel (width × depth) for best performance of the fuel cell.
Omozuwati L. Enearu, Yong Kang Chen, Christos Kalyvas, Ogbonda Douglas Chukwu

A Dynamic Equivalence Method Considering the Spatial Effect of Wind Farms

Abstract
In this paper, a dynamic and equivalent modeling method of large-scale wind farms based on clustering algorithm and measured data is proposed. According to the significant difference between wind speed and power curves in different wind turbine sets, the spatial effect is considered using the random sampling comparison method. In order to highlight the influence of spatial effect on the output power of wind farm, a simulation model consisting 20 wind turbines on the MATLAB/Simulink simulation platform is built. The result shows that the spatial effect cannot be neglected if the dynamic equivalent models of large-scale wind farm need a higher accuracy. In the actual wind farm, the measured wind speed and power data have to be taken into account the influence of the spatial effect. Therefore, the measured data of a wind farm is used as the clustering index according to K-means clustering analysis method. In an actual wind farm, 33 sets of UP77-1.5 MW wind turbines are grouped into 4 clusters. Each wind turbine set corresponds to an equivalent model, and takes into account the spatial effects of the sets. Finally, according to the comparison and error analysis of each model and the measured data, the rationality and correctness of the dynamic equivalent model proposed in this paper are verified. Compared with the traditional model, the model established in this paper is more accurate than the traditional model in the dynamic characteristics of the wind farm.
Cheng Guo, Delin Wang

Prescribed Performance Speed Control for Permanent Magnet Synchronous Motors

Abstract
A prescribed performance speed control method is proposed for permanent magnet synchronous motors (PMSM) to guarantee the prescribed error bound. A prescribed performance function (PPF) is used to characterize the convergence rate and steady-state error, such that the speed tracking error can be retained within a priori prescribed bound. To address the effects of unknown dynamics and bounded disturbances, a simple estimator is adopted to reconstruct the unknown system dynamics and the load inertia. The stability of the proposed control system is analyzed via the Lyapunov theory. The effectiveness of the estimator and the prescribed performance controller are demonstrated through simulations.
Bin Wang, Guanbin Gao, Tingli Su, Jing Na

Temperature Variation and Distribution in Tobacco Casing Cylinder Based on Infrared Thermal Imaging Detection

Abstract
To reveal the change of temperature field under the interaction of various flows in the tobacco cylinder during the tobacco primary processing, the procedure of lamina casing was studied. The temperature field in the casing cylinder was detected by infrared thermal imaging technology. The temperature variation of the lamina and the temperature distribution of casing cylinder were obtained under the action of multiphase flow. The casing process was simulated by ANSYS Fluent on the basis of the experimental data. The stationary distribution of the temperature field in the casing cylinder was obtained under the influence of different process air, process water, and casing flavour.
Yongda Ma, Ruibo Yuan, Banghua He, Honghai Jiang, Ze Liu, Yayu Huang, Jun Tang, Jing Luo, Bing Zhou, Junbing Qian, Yong Zhu, Lin Chen

Zero-Crossing Feature Extraction Based on Threshold Optimization for Rolling Element Bearing

Abstract
The rolling element bearings are widely used in mechanical transmission systems, whose failures are the most frequently encountered factors for machine breakdown. To effectively prevent the unexpected breakdown, it is important to extract the more efficient features to identify the bearings faults. The spectrum analysis for the bearing ball and inner fault recognition may not be suitable in this case. This paper proposed a threshold optimized zero-crossing feature extraction method, which calculates the Euclidean distance feature vector of the rolling bearing states. The optimizing observation window length and intervals number can be obtained, and the optimized feature vector is selected to establish the identification model. Experiment validates the effectiveness of the proposed method.
Qing Chen, Xing Wu, Tao Liu, Hua Li

A 3-DOF Parallel Mechanism Sensitivity Analysis and Parameter Sensitivity Analysis

Abstract
In this paper, the error analysis of 3-PUU three-dimensional translational parallel mechanism (the mechanism consists of three limbs, each of which consists of a prismatic pair and two universal hinges, this is called 3-PUU, P represents prismatic pair, U stands for universal hinges) is studied. First, the geometric error sources are isolated by using the vector chain method, and the relationship between the end position error and the geometric error sources is constructed. Second, the error of the branched chain can be accumulated to each branched chain on the x-, y- and z-axes, then the parallel mechanism has tight coupling and nonlinear characteristics. In order to acquire the influence aimed at the end position of the mechanism, each chain error values ∆x, ∆y, ∆z is taken to the direct equation, respectively. Consequently, different chain error would lead to different end position error of the mechanism, which provided a theoretical basis for designing mechanism.
Hongjun San, Jiupeng Chen, Junjie Zhao, Pengfei Li, Junsong Lei

Temperature-Predictive Control of Chromatograph

Abstract
Based on predictive control theory and transparent control structure, this paper presents that Dynamic Matrix Control (DMC) is used in temperature control system of chromatograph to deal with the time delay problem. Firstly, the principle of DMC algorithm is introduced. Then, the temperature control system of chromatograph is constructed in the form of multilayer hierarchical structure, including sectional PID and DMC. According to the MATLAB simulation research and experimentation results on the chromatograph, this method can effectively obtain a better tracking performance, compared with the PID control system, and is valuable in industry control field.
Yuzhen Zhang, Qing Li, Weicun Zhang
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