Adaptive Fuzzy Dynamic Surface Control for Nonlinear Systems with Time-Varying Input Delay and Sampled Data

Abstract

This paper studies fuzzy adaptive dynamic surface control strategy for nonlinear system with sampled data and time-varying input delay. By utilizing the approximated property of fuzzy logic systems (FLSs), a fuzzy estimator (FE) model is designed to identify the states of the original system, which is mainly used to provide information of estimation states to replace the sampled data of the nonlinear controlled system. In the proposed strategy, with the help of sampled-data activity, an integral term is designed to compensate the problem of time-varying input delay. Moreover, by invoking the dynamic surface control (DSC) technique, the problem of ‘explosion of complexity’ has been overcame. And the developed control strategy demonstrates that all signals of the controlled system are semi-globally uniformly ultimately bounded (SGUUB). Ultimately, two numerical simulation examples are given to prove the feasibility of the developed control method and theory.