Application of Neural Network in Control Problem

Author

Lin, Chih-Min

Author_Institution

Yuan Ze Univ., Taoyuan

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3465

Lastpage

3471

Abstract

This talk introduces several kinds of neural-network-based adaptive control systems. These control systems combine the advantages of neural network identification, adaptive control and robust control techniques. These neural networks include recurrent neural network (RNN), recurrent fuzzy neural network (RFNN), cerebellar model articulation controller (CMAC) and recurrent cerebellar model articulation controller (RCMAC). Moreover, their applications in control problems are demonstrated to illustrate the effectives of these control systems.

Keywords

adaptive control; cerebellar model arithmetic computers; control engineering computing; recurrent neural nets; robust control; adaptive control systems; control problem; neural network identification; recurrent cerebellar model articulation controller; recurrent fuzzy neural network; recurrent neural network; robust control; Adaptive control; Control systems; Fuzzy control; Fuzzy neural networks; Neural networks; Recurrent neural networks; Robust control; Uncertainty; Vehicle dynamics; Wheels; Adaptive control; CMAC; RCMAC; RFNN; RNN; Robust control;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370747

Filename

4370747