Adaptive control of nonlinear systems using neural networks

Fu-Chuang Chen*, Hassan K. Khalil

*Corresponding author for this work

Research output: Contribution to journalConference article

26 Scopus citations

Abstract

Layered neural networks are used in a nonlinear adaptive control problem. The plant is an unknown feedback-linearizable discrete-time system, represented by an input-output model. A state space model of the plant is obtained to define the zero dynamics, which are assumed to be stable. A linearizing feedback control is derived in terms of some unknown nonlinear functions. To identify these functions, it is assumed that they can be modeled by layered neural networks. The weights of the networks are updated and used to generate the control. A local convergence result is given. Computer simulations verify the theoretical result.

Original languageEnglish
Pages (from-to)1707-1712
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume3
DOIs
StatePublished - 1 Dec 1990
EventProceedings of the 29th IEEE Conference on Decision and Control Part 6 (of 6) - Honolulu, HI, USA
Duration: 5 Dec 19907 Dec 1990

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