Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems

Authors:
S. S. Ge;G. Y. Li;T. H. Lee
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore
Venue:
Automatica (Journal of IFAC)
Year:
2003

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Abstract

In this paper, both full state and output feedback adaptive neural network (NN) controllers are presented for a class of strict-feedback discrete-time nonlinear systems. Firstly, Lyapunov-based full-state adaptive NN control is presented via backstepping, which avoids the possible controller singularity problem in adaptive nonlinear control and solves the noncausal problem in the discrete-time backstepping design procedure. After the strict-feedback form is transformed into a cascade form, another relatively simple Lyapunov-based direct output feedback control is developed. The closed-loop systems for both control schemes are proven to be semi-globally uniformly ultimately bounded.