Intelligent Second-Order Sliding-Mode Control for Chaotic Tracking Problem

The behavior of a chaotic dynamic system is extremely sensitive to the system parameters and initial conditions. In this paper, a recurrent fuzzy neural network (RFNN) is used to online approximate the unknown nonlinear term of chaotic system dynamics with a good accuracy. Meanwhile, an intelligent second-order sliding-mode control (ISSMC) system is proposed for a chaotic dynamic system with high accuracy tracking response. A neural controller and a robust compensator are designed in the proposed ISSMC system. Because of the ISSMC system uses integration method to obtain the actual control signal, the chattering phenomenon can be removed effectively. Further, the controller parameter adaptation laws are derived based on the Lyapunov function, so that the system stability of the closed-loop system can be guaranteed. Finally, the proposed ISSMC method is successfully applied to the chaotic tracking control problem.