Dynamic Modeling and Neural Network Self-tuning PID Control Design for a Linear Motor Driving Platform

作者：Hsieh Sheng Ping^*; Hwang Thong Shing

来源：IEEJ Transactions on Electrical and Electronic Engineering, 2010, 5(6): 701-707.

DOI：10.1002/tee.20595

• balancing realization
• identification
• linear motor self-tuning PID
• wavelet neural network

The purpose of this paper is to design a wavelet neural network self-tuning proportional integral derivative (PID) controller for solving the problem of fast changing payload in a linear motor In the 6-DOF platform system The wavelet neural network PID controller demonstrates the special capabilities of last response and self-tuning. A practical system identification method is proposed to identify the dynamic model of a linear motor by using the balancing realization theorem and inverse discrete Fourier transform The experimental results of the real-time software simulation and hardware-in-the-loop simulation demonstrate the novel ability of self-tuning PID controller for adapting the quick load change in the forcer of linear motor.

• 出版日期2010-11