Nonlinear adaptive control of interconnected systems using neural networks

Author

Huang, S.N. ; Tan, K.K. ; Lee, T.H.

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

Volume

17

Issue

1

fYear

2006

Firstpage

243

Lastpage

246

Abstract

In this letter, we solve the problem of decentralized adaptive asymptotic tracking for a class of large scale systems with significant nonlinearities and uncertainties. Neural networks (NNs) are used as a control part to cancel the effect of the unknown nonlinearity. Semiglobal asymptotic stability results are obtained and the tracking error converges to zero.

Keywords

adaptive control; asymptotic stability; control nonlinearities; large-scale systems; neurocontrollers; nonlinear control systems; uncertain systems; decentralized asymptotic tracking; interconnected systems; large-scale systems; neural networks; nonlinear adaptive control; semiglobal asymptotic stability; Adaptive control; Centralized control; Control systems; Interconnected systems; Large-scale systems; Neural networks; Nonlinear control systems; Power system interconnection; Power system stability; Uncertainty; Adaptive control; interconnected systems; neural networks (NNs); stability; Algorithms; Artificial Intelligence; Humans; Linear Models; Models, Neurological; Neural Networks (Computer); Neurons; Pattern Recognition, Automated; Skin Pigmentation; Synapses;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2005.857948

Filename

1593708