Model reference adaptive control for multi-input multi-output nonlinear systems using neural networks

Author

Phuah, Jiunshian ; Lu, Jianming ; Yahagi, Takashi

Author_Institution

Graduate Sch. of Sci. & Technol., Chiba Univ., Japan

Volume

4

fYear

2001

fDate

2001

Firstpage

303

Abstract

Presents a method of MRAC (model reference adaptive control) for multi-input multi-output (MIMO) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of a model reference adaptive controller and the output of the NN. The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems

Keywords

MIMO systems; compensation; control nonlinearities; discrete time systems; model reference adaptive control systems; multilayer perceptrons; multivariable control systems; neurocontrollers; nonlinear control systems; MIMO systems; MRAC; model reference adaptive control; multi-input multi-output nonlinear systems; neural networks; nonlinearity compensation; Adaptive control; Control nonlinearities; Control system synthesis; Error correction; MIMO; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Regulators;

fLanguage

English

Publisher

ieee

Conference_Titel

Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on

Conference_Location

Beijing

Print_ISBN

0-7803-7010-4

Type

conf

DOI

10.1109/ICII.2001.983836

Filename

983836