Nonlinear control with linearized models and neural networks

Hussain, M.A. and Allwright, J.C. and Kershenbaum, L.S. (1995) Nonlinear control with linearized models and neural networks. In: Proceedings of the 4th International Conference on Artificial Neural Networks, 1995, Cambridge, UK.

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Abstract

A nonlinear control strategy involving a geometric feedback controller and adaptive approximation of the plant is presented. The plant is approximated by a linearized model and a neural network which approximates the higher order error terms. Online adaptation of the network is performed using steepest descent with a dead zone function. The proposed strategy is applied to two case studies for output tracking of set points. The results show good tracking comparable with utilizing the actual model of the plant (usually unknown) and better than that obtained when using the linearized model alone.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Conference code: 43331 Export Date: 5 March 2013 Source: Scopus CODEN: IECPB Language of Original Document: English Correspondence Address: Hussain, M.A.; Imperial Coll, London, United Kingdom Sponsors: IEE
Uncontrolled Keywords: Adaptive systems, Approximation theory, Control equipment, Feedback control, Linearization, Mathematical models, Neural networks, Poles and zeros, State space methods, Vectors, Geometric feedback controller, Online adaptation, Nonlinear control systems.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 11 Jul 2013 01:27
Last Modified: 11 Jul 2013 01:27
URI: http://eprints.um.edu.my/id/eprint/7099

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