An Identifier-Based Control Method in Dynamic Tracking Neuro-Fuzzy Control System

Author

Xu, Kaijun ; Li, Yang ; Xu, Weitao ; Xu, Yang

Author_Institution

Intell. Control & Dev. Center, Southwest Jiaotong Univ., Chengdu, China

Volume

5

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

71

Lastpage

75

Abstract

It is difficult to realize dynamic control for some complex nonlinear processes which are operated in different environments and when operation conditions are changed frequently. In this paper we propose an identifier-based control method in dynamic tracking neuro-fuzzy control system. The dynamic tracking neuro-fuzzy control (DTNFC) system is comprised of two neural networks and a system identification network. The system identification network is used to identify the output of the manipulator system, and one of the dynamic neural networks is employed to learn the weighting factor of the fuzzy logic neural network, the other is control the manipulator system. The identifier combines two parts: performance index and selector. A hysteresis switching algorithm is applied to select the best model.

Keywords

fuzzy control; fuzzy neural nets; identification; learning systems; manipulators; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; time-varying systems; tracking; complex nonlinear process; dynamic tracking neuro-fuzzy control system identification; hysteresis switching algorithm; manipulator control system; performance index; performance selector; weight factor learning; Adaptive control; Artificial neural networks; Control systems; Fuzzy logic; Intelligent control; Manipulator dynamics; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.809

Filename

5170499