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JACIII Vol.25 No.2 pp. 162-169
doi: 10.20965/jaciii.2021.p0162
(2021)

Paper:

Repetitive Control Based on Multi-Stage PSO Algorithm with Variable Intervals for T–S Fuzzy Systems

Yibing Wang*,**, Manli Zhang*,**, Min Wu*,**,***,†, and Luefeng Chen*,**,***

*School of Automation, China University of Geosciences
No.388 Lumo Road, Hongshan, Wuhan 430074, China

**Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan, Wuhan 430074, China

***Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education
No.388 Lumo Road, Hongshan, Wuhan 430074, China

Corresponding author

Received:
October 2, 2020
Accepted:
November 26, 2020
Published:
March 20, 2021
Keywords:
two-dimensional repetitive control, multi-stage particle swarm optimization algorithm with variable intervals, Takagi–Sugeno fuzzy model, permanent magnet synchronous motor
Abstract
Repetitive Control Based on Multi-Stage PSO Algorithm with Variable Intervals for T–S Fuzzy Systems

Flowchart of improved PSO algorithm

This study presents a repetitive control method based on a multi-stage particle swarm optimization (PSO) algorithm with variable intervals to enhance the tracking performance of Takagi–Sugeno (T–S) fuzzy systems. First, a T–S fuzzy model is used to describe a nonlinear system. A modified repetitive control structure with two repetitive loops guarantees the tracking accuracy of periodic signals. Taking advantage of the two-dimensional (2D) property with continuous control and discrete learning, a continuous-discrete 2D model is presented to describe the nonlinear repetitive control system. Next, a multi-stage PSO algorithm with variable intervals searches for the best parameter combination in the linear matrix inequality-based stability condition to regulate the control and learning actions, which avoids a suboptimal solution and guarantees high control accuracy. Finally, an application to control the speed of synchronous motor with a permanent magnet demonstrates the validity of the method, and comparisons with related methods show its superiority.

Cite this article as:
Yibing Wang, Manli Zhang, Min Wu, and Luefeng Chen, “Repetitive Control Based on Multi-Stage PSO Algorithm with Variable Intervals for T–S Fuzzy Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.25, No.2, pp. 162-169, 2021.
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Last updated on May. 04, 2021