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

Chao Du, Zhonggang Yin, Yanping Zhang, Xiangdong Sun, Yanru Zhong

IEEE Transactions on Power Electronics · 2018 · 109 citations · 26 references

Concepts

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.

References

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