Brief paper: Novel adaptive neural control design for nonlinear MIMO time-delay systems
Automatica (Journal of IFAC)
Sampled-data adaptive NN tracking control of uncertain nonlinear systems
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
An Adaptive NN Controller with Second Order SMC-Based NN Weight Update Law for Asymptotic Tracking
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Information Sciences: an International Journal
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A class of uncertain nonlinear systems that are additionally driven by unknown covariance noise is considered. Based on the backstepping technique, adaptive neural control schemes are developed to solve the output tracking control problem of such systems. As it is proven by stability analysis, the proposed controller guarantees that all the error variables are bounded with desired probability in a compact set while the tracking error is mean-square semiglobally uniformly ultimately bounded (M-SGUUB). The tracking performance and the effectiveness of the proposed design are evaluated by simulation results.