Adaptive backstepping tracking control using self-organizing fuzzy neural network

Abstract

This papers proposes an adaptive backstepping tracking control (ABTC) via self-organizing fuzzy neural network (SOFNN) approach. The proposed ABTC system is comprised of a backstepping tracking controller and an L, controller. The backstepping tracking controller containing a SOFNN identifier is the principal controller, and the L, controller is designed to achieve a tracking performance with desired attenuation level. The SOFNN identifier is used to online estimate the system dynamics with structure and parameter learning. Finally, the proposed ABTC is applied to control a chaotic dynamic system. The simulation results verify that the proposed ABTC system can achieve favorable tracking performance by incorporating of neural network approach and adaptive backstepping control technique.