The Permanent Magnet Synchronous Linear Motor Position Control Based on Fuzzy Neural Network

Author

Li Cailin ; Wang Dongmei

Author_Institution

Sch. of Mech. & Electr., Guilin Univ. of Electron. & Technol., Guilin, China

fYear

2013

fDate

9-11 Sept. 2013

Firstpage

602

Lastpage

606

Abstract

A position servo control system based on fuzzy neural network (FNN) is proposed to make the permanent magnet synchronous linear motor(PMLSM) to track the given locus precisely. In the proposed system, Back-Propagation (BP) neural network algorithm based on dynamic structure is employed to change the nodes of hidden layer in learning process and improve the system control effect. The experimental results show the position servo system has a small overshot and good position precision.

Keywords

backpropagation; electric machine analysis computing; fuzzy neural nets; linear synchronous motors; machine control; permanent magnet motors; position control; servomechanisms; BP neural network algorithm; FNN; PMLSM; back-propagation neural network algorithm; dynamic structure; fuzzy neural network; learning process; permanent magnet synchronous linear motor position control; position servo control system; Fuzzy control; Fuzzy neural networks; Heuristic algorithms; Permanent magnet motors; Servosystems; Synchronous motors; dynamic structure; fuzzy neural network; permanent magnet synchronous linear motor;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networking and Collaborative Systems (INCoS), 2013 5th International Conference on

Conference_Location

Xi´an

Type

conf

DOI

10.1109/INCoS.2013.112

Filename

6630495