Neural Network Control Design for Large-Scale Systems with Higher-Order Interconnections

Abstract

AbstractA 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 ErrorRadial Basis Neural NetworkWeight Estimation ErrorAdaptive Decentralize ControlBasis Neural Network ControlThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.