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A hyperstable neural network for the modelling and control of nonlinear systems |
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| Authors: | K Warwick Q M Zhu Z Ma |
| Affiliation: | (1) Department of Cybernetics, University of Reading, PO Box 225, RG6 6AY Whiteknights, Reading, UK;(2) Department of Mechanical and Electrical Engineering, Aston University, Aston Triangle, B4 7ET Birmingham, UK;(3) Center for Engineering Research Technikon Natal, PO Box 953, 4000 Durban, South Africa |
| Abstract: | A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given. |
| Keywords: | Computer control neural networks nonlinear systems adaptive control |
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