Neural Network Control Design for Large-Scale Systems with Higher-Order Interconnections
A decentralized neural network controller for a class of large-scale nonlinear systems with the higher-order interconnections is proposed. The neural networks (NNs) are used to cancel the effects of unknown subsystems, while the robustifying terms are used to counter the effects of the interconnections. Semi-global asymptotic stability results are obtained and the tracking error converges to zero.
KeywordsTracking Error Radial Basis Neural Network Weight Estimation Error Adaptive Decentralize Control Basis Neural Network Control
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