A method of simple adaptive control for MIMO nonlinear continuous-time systems using multifraction neural network

Author

Yasser, Muhammad ; Phuah, Jiunshian ; Jianming Lu ; Yahagi, Takashi

Author_Institution

Grad. Sch. of Sci. & Tech., Chiba Univ., Japan

Volume

1

fYear

2003

fDate

20-24 July 2003

Firstpage

23

Abstract

This paper presents a method of continuous-time simple-adaptive control (SAC) for multi-input multi-output (MIMO) nonlinear systems using multifraction neural networks. The control input is given by the sum of the output of the simple adaptive controller and the output of the multifraction neural network is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual SAC. The role of the multifraction neural network is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.

Keywords

MIMO systems; adaptive control; continuous time systems; neural nets; neurocontrollers; nonlinear control systems; MIMO nonlinear continuous-time systems; linearized model; multifraction neural network; multiinput multioutput; nonlinear control systems; output error minimization; plant dynamics nonlinearity; simple adaptive control; Adaptive control; Control nonlinearities; Control system synthesis; Control systems; Error correction; MIMO; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Intelligent Mechatronics, 2003. AIM 2003. Proceedings. 2003 IEEE/ASME International Conference on

Print_ISBN

0-7803-7759-1

Type

conf

DOI

10.1109/AIM.2003.1225066

Filename

1225066