A Neural Network Based Robust Control of Nonlinear Systems With a General Set of Uncertainties

摘要

Based on the RBF neural network, a novel estimator is presented for unmodeled dynamics and a robust adaptive control scheme is proposed for a class of uncertain nonlinear systems with a general set of uncertainties in this paper. A class of more extended semi-strict feedback form system is studied in this paper. With the recent results, it is impossible to design the robust controller for the system. A novel estimator is constructed to estimate the unmeasured states of the unmodeled dynamic. With the novel estimator and the RBF based adaptive backstepping, the overall scheme achieves robust regulation of the output while maintaining boundedness of all the signals and states.