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Proceedings Paper

Compound intelligent control system combining fuzzy control with neural networks in a permanent magnetic synchronous motor
Author(s): Zhiyuan Zhang; Weili Li; Taifu Li
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Paper Abstract

An AC motor belongs to the category of a controlled object that is multi-variable, nonlinear and strong correlation, complex to mathematical model, and whose control performance is affected by a time-changing parameter. Therefore, it is very difficult to obtain the desired static and dynamic characteristic through a general fixed regulator. In this paper, the authors present a compound intelligent control strategy, combined with a neural network and fuzzy control. Considering that a neural network is good at self-learning, and a single fuzzy control algorithm is rapid in its response characteristics, the compound control strategy can compensate for a disadvantage of fuzzy control, which is associated with poor stability and precision and also requires solving a puzzle in the time-changing parameters in the controlled object. On the basis of a dynamic model of the permanent magnetic synchronous motor and its working principle, the authors designed the block diagram of a control system, combined a neural PID control and fuzzy control, and studied the corresponding control algorithm in detail. The simulation results show that the compound intelligent control system is good in dynamic performance and robustness.

Paper Details

Date Published: 2 May 2006
PDF: 7 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60421S (2 May 2006); doi: 10.1117/12.664629
Show Author Affiliations
Zhiyuan Zhang, Chongqing Institute of Technology (China)
Weili Li, Chongqing Institute of Technology (China)
Taifu Li, Chongqing Institute of Technology (China)


Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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