An enhanced neural adaptive control scheme for discrete-time non-affine nonlinear systems

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dc.contributor.authorMazumdar, S.K.
dc.contributor.authorLim, C.C.
dc.date.issued1995
dc.description.abstractAn adaptive control procedure utilising neural networks is presented. The method is based on the model reference control technique and can be applied to multi-input multi-output discrete-time nonlinear systems of unknown structure.Multi-layered neural networks are used to approximate the plant Jacobian and synthesise the controller. An enhanced reference model is proposed that generates the desired output response and enables sufficient conditions for the convergence of the tracking error between the desired output and controlled output to be derived. Lyapunov theory is used to show that the overall system is stable. Simulation studies demonstrate that the proposed scheme performs well even in the presence of dynamic perftubations.
dc.description.statementofresponsibilityMazumdar SK, Lim CC
dc.identifier.citationAustralian Journal of Intelligent Information Processing Systems, 1995; 2(4):20-27
dc.identifier.issn1321-2133
dc.identifier.orcidLim, C.C. [0000-0002-2463-9760]
dc.identifier.urihttp://hdl.handle.net/2440/2316
dc.language.isoen
dc.publisherCentre of Intelligent Information Processing Systems
dc.rightsCopyright status unknown
dc.titleAn enhanced neural adaptive control scheme for discrete-time non-affine nonlinear systems
dc.typeJournal article
pubs.publication-statusPublished

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