Adaptive control of multi-variables nonlinear system based on artificial neural network

Author

Gong, Dunwei ; Zhou, Yong

Author_Institution

Coll. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Jiangsu, China

Volume

1

fYear

2001

fDate

2001

Firstpage

64

Abstract

In this paper, the adaptive control of a multivariable nonlinear system based on artificial neural networks is put forth. A three-layer diagonal recurrent neural network is used to identify the system. The neural net´s structure is simple, the number of networks is small and it can also identify the system better. A three-layer feedforward neural network is applied to control the system. The method to train neural network is simple, so it improves response speed to desired inputs. The strategy is applied to the control of a nonlinear dynamic system. Simulation studies show its efficiency

Keywords

adaptive control; control system analysis; control system synthesis; feedforward neural nets; learning (artificial intelligence); multivariable control systems; neurocontrollers; nonlinear control systems; recurrent neural nets; adaptive control; control design; control simulation; multivariable nonlinear system; nonlinear dynamic system; response speed; three-layer diagonal recurrent neural network; three-layer feedforward neural network; training; Adaptive control; Artificial neural networks; Control systems; Feedforward neural networks; Feedforward systems; Neural networks; Neurons; Nonlinear control systems; Nonlinear systems; Recurrent neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on

Conference_Location

Pusan

Print_ISBN

0-7803-7090-2

Type

conf

DOI

10.1109/ISIE.2001.931756

Filename

931756