Adaptive Nonparametric Evolving Fuzzy Controller for Nonlinear Uncertain Systems with Dead Zone

This chapter presents an adaptive nonparametric evolving fuzzy controller for uncertain nonlinear systems with dead zone. The unknown nonlinearities caused by the dead zone are approximated using the EFSs based on data clouds, based on which the controller is designed via the Backstepping procedure. The EFSs based on data clouds impose the local and global density as the learning schemes to adapt the structure of the controller using the information extracted from nonstationary data streams. The stable parameter adjustment laws with projection operator are derived under the Lyapunov theorem to update the parameters of the controller. To further reduce the influence of the approximation errors brought by the data clouds-based EFS approximators, a sliding mode control term is designed to augment the controller. The stability of the proposed controller is proven under the Lyapunov synthesis, and its effectiveness is verified by the simulation results.