Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems
The authors present both full state and output feedback adaptive neural network controllers for a class of strict-feedback discrete-time nonlinear systems, and they provide Lyapunov-based full-state adaptive neural network control 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.
scientific article; zbMATH DE number 1963701