An approximate design of the prescribed performance control for uncertain discrete-time nonlinear strict-feedback systems
Toshio Yoshimura
Abstract
This paper presents an approximate prescribed performance control for a class of uncertain discrete-time nonlinear strict-feedback systems with full state constraints. The observation of the states is taken with a set of independent random measurement noises. The approximate prescribed performance control is proposed as follows. In the tracking error equations on the adaptive fuzzy backstepping control, the future virtual controls are replaced as the current virtual controls to obtain the actual control in a simple structure. The nonlinear uncertainties included in the systems are approximated as the fuzzy logic systems, and the number of the fuzzy IF–THEN rules is reduced based on the simplified extended single input rule modules. The estimates for the un-measurable states and the adjustable parameters are obtained by using the proposed approximate estimator. The estimation errors are proved to be uniformly ultimately bounded. The effectiveness of the proposed approach is indicated by the simulation experiment of a simple numerical system.