Research on Autodisturbance-Rejection Control of Induction Motors Based on an Ant Colony Optimization Algorithm

An autodisturbance-rejection control (ADRC) of an induction motor based on an ant colony optimization (ACO) algorithm is proposed in this paper, in order to realize the precise decoupling of the induction motor and the disturbance compensation. A novel control method employs ACO as an automatic tune mechanism for an ADRC controller. According to the feedback information from the induction motor, an optimal solution can be achieved via the optimization mechanism and self-learning ability of ACO after the iterative calculation; therefore, the reliance of the ADRC controller on parameters can be reduced. The simulation and experimental results indicate that the robustness of the proposed optimal design method for ADRC is better than that of the conventional ADRC when the disturbances occur and that the method is feasible and effective.

[1]  Pierre Borne,et al.  Tuning PID Controller Using Multiobjective Ant Colony Optimization , 2012, Appl. Comput. Intell. Soft Comput..

[2]  Pierre Sicard,et al.  PID controllers and anti-windup systems tuning using ant colony optimization , 2013, 2013 15th European Conference on Power Electronics and Applications (EPE).

[3]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[4]  Norbert C. Cheung,et al.  Disturbance and Response Time Improvement of Submicrometer Precision Linear Motion System by Using Modified Disturbance Compensator and Internal Model Reference Control , 2013, IEEE Transactions on Industrial Electronics.

[5]  Hannu Tenhunen,et al.  Using Ant Colony System to Consolidate VMs for Green Cloud Computing , 2015, IEEE Transactions on Services Computing.

[6]  Zhu Jianhua,et al.  Auto-disturbances-rejection Controller and it′s Application in Fast Following Synchronizer of Generators , 2003 .

[7]  Chia-Feng Juang,et al.  Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments , 2015, IEEE Transactions on Cybernetics.

[8]  Eun-Kyung Kim,et al.  Adaptive PID Speed Control Design for Permanent Magnet Synchronous Motor Drives , 2015, IEEE Transactions on Power Electronics.

[9]  Xiu Yao,et al.  Load Modeling and Identification Based on Ant Colony Algorithms for EV Charging Stations , 2015, IEEE Transactions on Power Systems.

[10]  Hui Wang,et al.  An Adaptive Support Vector Machine-Based Workpiece Surface Classification System Using High-Definition Metrology , 2015, IEEE Transactions on Instrumentation and Measurement.

[11]  Jeng-Tze Huang,et al.  Smooth Switching Robust Adaptive Control for Omnidirectional Mobile Robots , 2015, IEEE Transactions on Control Systems Technology.

[12]  Shiyou Yang,et al.  A Modified Particle Swarm Optimization Algorithm for Global Optimizations of Inverse Problems , 2016, IEEE Transactions on Magnetics.

[13]  Li Sun,et al.  Nonlinear Speed Control for PMSM System Using Sliding-Mode Control and Disturbance Compensation Techniques , 2013, IEEE Transactions on Power Electronics.

[14]  Ming Cheng,et al.  Sensorless SVPWM-FADTC of a New Flux-Modulated Permanent-Magnet Wheel Motor Based on a Wide-Speed Sliding Mode Observer , 2015, IEEE Transactions on Industrial Electronics.

[15]  Jae-Duck Lee,et al.  An Event-Oriented Method for Online Load Modeling Based on Synchrophasor Data , 2015, IEEE Transactions on Smart Grid.

[16]  Yongchang Zhang,et al.  Two-Vector-Based Model Predictive Torque Control Without Weighting Factors for Induction Motor Drives , 2016, IEEE Transactions on Power Electronics.

[17]  Bin Li,et al.  Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks , 2015, IEEE Transactions on Consumer Electronics.

[18]  Jie Li,et al.  Robust Speed Control of Induction Motor Drives Using First-Order Auto-Disturbance Rejection Controllers , 2012, IEEE Transactions on Industry Applications.

[19]  Takahiro Hara,et al.  A Multi-Objective Optimization Scheduling Method Based on the Ant Colony Algorithm in Cloud Computing , 2015, IEEE Access.

[20]  Wei Xue,et al.  Active Disturbance Rejection Control for a Flywheel Energy Storage System , 2015, IEEE Transactions on Industrial Electronics.

[21]  R. V. Carrillo-Serrano,et al.  Estimating rotor parameters in induction motors using high-order sliding mode algorithms , 2015 .

[22]  Wei Shao,et al.  An Improved Multi-Objective Genetic Algorithm for Large Planar Array Thinning , 2016, IEEE Transactions on Magnetics.

[23]  Yan-Fei Liu,et al.  A new robust control to improve the dynamic performance of induction motors , 2001, 2001 IEEE 32nd Annual Power Electronics Specialists Conference (IEEE Cat. No.01CH37230).

[24]  Yongchang Zhang,et al.  Generalized Two-Vector-Based Model-Predictive Torque Control of Induction Motor Drives , 2015, IEEE Transactions on Power Electronics.

[25]  Yogesh V. Hote,et al.  Load Frequency Control in Power Systems via Internal Model Control Scheme and Model-Order Reduction , 2013, IEEE Transactions on Power Systems.

[26]  Yang Zhao,et al.  Active disturbance rejection control for trajectory tracking of space manipulator flexible joint , 2011, Proceedings of the 30th Chinese Control Conference.

[27]  Yuanqing Xia,et al.  Active Disturbance Rejection Position Control for a Magnetic Rodless Pneumatic Cylinder , 2015, IEEE Transactions on Industrial Electronics.

[28]  George Tambouratzis,et al.  Using an Ant Colony Metaheuristic to Optimize Automatic Word Segmentation for Ancient Greek , 2009, IEEE Transactions on Evolutionary Computation.

[29]  Chao Ying Liu,et al.  Parameters self-adaptive fuzzy controller based on genetic algorithm , 2007, 2007 IEEE International Conference on Grey Systems and Intelligent Services.

[30]  Pierre Sicard,et al.  ACO based controller and anti-windup tuning for motion systems with flexible transmission , 2013, 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).

[31]  Zongxia Jiao,et al.  Adaptive Robust Control of DC Motors With Extended State Observer , 2014, IEEE Transactions on Industrial Electronics.

[32]  Zhenxiong Zhou,et al.  Permanent magnet synchronous motor control system based on auto disturbances rejection controller , 2011, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC).

[33]  Miao Li,et al.  A Hyperheuristic Approach for Intercell Scheduling With Single Processing Machines and Batch Processing Machines , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[34]  Yongchang Zhang,et al.  Generalized two-vectors-based model predictive torque control of induction motor drives , 2014, 2014 IEEE Energy Conversion Congress and Exposition (ECCE).

[35]  Ali Saghafinia,et al.  Adaptive Fuzzy Sliding-Mode Control Into Chattering-Free IM Drive , 2015, IEEE Transactions on Industry Applications.

[36]  Chia-Feng Juang,et al.  Evolutionary Robot Wall-Following Control Using Type-2 Fuzzy Controller With Species-DE-Activated Continuous ACO , 2013, IEEE Transactions on Fuzzy Systems.

[37]  Yunhua Li,et al.  Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II , 2015, IEEE Transactions on Power Delivery.

[38]  Andrea De Lucia,et al.  Improving Multi-Objective Test Case Selection by Injecting Diversity in Genetic Algorithms , 2015, IEEE Transactions on Software Engineering.

[39]  Jianming Yao,et al.  Scheduling Optimization in the Mass Customization of Global Producer Services , 2015, IEEE Transactions on Engineering Management.

[40]  Yongchang Zhang,et al.  Model Predictive Torque Control of Induction Motor Drives With Optimal Duty Cycle Control , 2014, IEEE Transactions on Power Electronics.

[41]  Yongchang Zhang,et al.  Performance evaluation of an improved model predictive control with field oriented control as a benchmark , 2017 .

[42]  Mrdjan Jankovic,et al.  Composite Adaptive Internal Model Control and Its Application to Boost Pressure Control of a Turbocharged Gasoline Engine , 2015, IEEE Transactions on Control Systems Technology.

[43]  Gang George Yin,et al.  Analyzing Convergence and Rates of Convergence of Particle Swarm Optimization Algorithms Using Stochastic Approximation Methods , 2013, IEEE Transactions on Automatic Control.

[44]  Yongchang Zhang,et al.  Model-Predictive Control of Induction Motor Drives: Torque Control Versus Flux Control , 2016, IEEE Transactions on Industry Applications.

[45]  Huimin Wang,et al.  Parameter tuning of particle swarm optimization by using Taguchi method and its application to motor design , 2014, 2014 4th IEEE International Conference on Information Science and Technology.

[46]  Arumugam Nallanathan,et al.  Efficient and Robust Cluster Identification for Ultra-Wideband Propagations Inspired by Biological Ant Colony Clustering , 2015, IEEE Transactions on Communications.