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This paper concerns the problem of stabilizing fuzzy chaotic systems via the viewpoint of the edgewise subdivision approach. Firstly, a new edgewise subdivision algorithm is proposed to implement the simplex edgewise subdivision which divides the overall fuzzy chaotic systems into a lot of sub-systems by a kind of algebraic description. These sub-systems have the same volume and shape characteristics. Secondly, a novel kind of control scheme which switches by the transfer of different operating sub-systems is proposed to achieve convergent stabilization conditions for the underlying controlled fuzzy chaotic systems. Finally, a numerical example is given to demonstrate the validity of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, the impulsive synchronization problem of Lü chaotic systems is investigated by using a novel hybrid controller. The proposed hybrid controller is composed of a single controller and impulsive controller. Using the impulsive theory and the novel hybrid controller, some sufficient conditions are derived for the synchronization of Lü chaotic systems. Numerical simulation example is provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional single controller method and impulsive controller method. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an adaptive self-organizing Hermite-polynomial-based neural control (ASHNC) system which is composed of a neural controller and a supervisor compensator. The neural controller uses a self-organizing Hermite-polynomial-based neural network (SHNN) to approximate an ideal feedback controller. For the SHNN, the developed self-organizing approach is clearly and easily used for real-time systems and the parameter learning ability is effective with high convergence precision and fast convergence time. The supervisor compensator is designed to eliminate the approximation error between the neural controller and ideal feedback controller without chattering phenomena. Moreover, a proportional–integral (PI) type adaptation law is derived based on the Lyapunov stability theory; thus not only the system stability of the control system can be guaranteed but also the convergence of the tracking error can be speeded up. Finally, the proposed ASHNC system is applied to a chaotic system. Simulation results demonstrate that the proposed ASHNC system can achieve favorable control performance. [Copyright &y& Elsevier]