Fuzzy self-tuning decoupling control based on neural network of three-motor drive system

被引：2

作者：

Zhang, Hao ^{[1
,2
]}

Yu, Kun ^{[2
]}

Liu, Guo-Hai ^{[2
]}

Hu, De-Shui ^{[2
]}

Zhao, Wen-Xiang ^{[2
]}

机构：

[1] Key Laboratory of Measurement and Control of Complex System of Engineering of Ministry of Education, Southeast University

[2] School of Electrical and Information Engineering, Jiangsu University

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2013年 / 30卷 / 09期

关键词：

Fuzzy self-tuning control; Neural network generalized inverse; Starting characteristics; Three-motor drive;

D O I：

10.7641/CTA.2013.12126

中图分类号：

学科分类号：

摘要：

Multi-motor drive system is a multi-input multi-output (MIMO), nonlinear and strong-coupling system. It is applied to many drive fields where high precision coordinated control is of importance, such as the electric vehicle drive, urban rail transit, and printing. In this paper, a new control strategy is proposed for decoupling the speed and the tension of the three-motor drive system, in which the key is to incorporate the fuzzy self-tuning control with back-propagation (BP) neural network generalized inverse (NNGI). The pseudo-linear composite system is formed by connecting NNGI in series with the original system; and then, the fuzzy self-tuning control method is introduced to this pseudo-linear system. Simulation results demonstrate that the proposed strategy can effectively decouple speeds and tensions, and transform the three-motor drive system into several single-input single-output (SISO) linear subsystems with open-loop stability. This system has obvious superiority in rapid response speed, low overshoot, short transient time and good tracking effect, which help to improve the starting characteristics of the system and decrease the system oscillation.

引用

页码：1178 / 1186

页数：8

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