Research on Active Disturbance Rejection Control With Parameter Autotune Mechanism for Induction Motors Based on Adaptive Particle Swarm Optimization Algorithm With Dynamic Inertia Weight

An active disturbance rejection control (ADRC) of induction motor based on an adaptive particle swarm optimization (APSO) algorithm is proposed in this paper, in order to realize the precise decoupling of induction motor and the disturbance compensation. The novel control method employs APSO as the...

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Vydané v:IEEE transactions on power electronics Ročník 34; číslo 3; s. 2841 - 2855
Hlavní autori: Du, Chao, Yin, Zhonggang, Zhang, Yanping, Liu, Jing, Sun, Xiangdong, Zhong, Yanru
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Active control
Active disturbance rejection control (ADRC)
Adaptive algorithms
Adaptive control
adaptive particle swarm
Automatic control
Decoupling
induction motor (IM)
Induction motors
Inertia
Mathematical model
Optimization
Optimization algorithms
parameter optimization
Parameters
Particle swarm optimization
Performance analysis
Rejection
Robust control
Robustness
Weight
ISSN:0885-8993, 1941-0107
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Abstract An active disturbance rejection control (ADRC) of induction motor based on an adaptive particle swarm optimization (APSO) algorithm is proposed in this paper, in order to realize the precise decoupling of induction motor and the disturbance compensation. The novel control method employs APSO as the automatic tune mechanism for ADRC controller. According to the feedback information of induction motor, an optimal solution can be achieved via the optimization mechanism and self-learning ability of APSO, so the reliance of ADRC controller on parameters can be reduced. In order to obtain the better optimization solution more efficient, the aggregation degree and the evolution speed are introduced into the APSO to dynamically modify the inertia weight based on the practical optimization process. Experimental results indicate that the robustness of the proposed optimal design method for ADRC is better than the conventional ADRC when the disturbances occur, and the method is feasible and effective.
AbstractList An active disturbance rejection control (ADRC) of induction motor based on an adaptive particle swarm optimization (APSO) algorithm is proposed in this paper, in order to realize the precise decoupling of induction motor and the disturbance compensation. The novel control method employs APSO as the automatic tune mechanism for ADRC controller. According to the feedback information of induction motor, an optimal solution can be achieved via the optimization mechanism and self-learning ability of APSO, so the reliance of ADRC controller on parameters can be reduced. In order to obtain the better optimization solution more efficient, the aggregation degree and the evolution speed are introduced into the APSO to dynamically modify the inertia weight based on the practical optimization process. Experimental results indicate that the robustness of the proposed optimal design method for ADRC is better than the conventional ADRC when the disturbances occur, and the method is feasible and effective.
Author Zhang, Yanping
Du, Chao
Yin, Zhonggang
Liu, Jing
Sun, Xiangdong
Zhong, Yanru
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SubjectTerms Active control
Active disturbance rejection control (ADRC)
Adaptive algorithms
Adaptive control
adaptive particle swarm
Automatic control
Decoupling
induction motor (IM)
Induction motors
Inertia
Mathematical model
Optimization
Optimization algorithms
parameter optimization
Parameters
Particle swarm optimization
Performance analysis
Rejection
Robust control
Robustness
Weight
Title Research on Active Disturbance Rejection Control With Parameter Autotune Mechanism for Induction Motors Based on Adaptive Particle Swarm Optimization Algorithm With Dynamic Inertia Weight
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