Abstract:
Based on the approximation capability and generalization property of the backpropagation neural networks (BPNNs) for nonlinear mapping on a compact set, this paper presen...Show MoreMetadata
Abstract:
Based on the approximation capability and generalization property of the backpropagation neural networks (BPNNs) for nonlinear mapping on a compact set, this paper presents a novel approach for designing adaptive neurocontroller (ANC) for unknown multivariable discrete nonlinear systems in general form. The key ideas of the proposed control strategy are of applying the Clarke's one-step-ahead weighted predictive control performance index and linearizing the feedforward BPNNs identifier models. Simulation results demonstrate the effectiveness of the new adaptive neural control scheme.<>
Date of Conference: 14-16 December 1994
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-1968-0
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