Robust predictive synchronization of uncertain fractional-order time-delayed chaotic systems

Abstract

In this paper, a novel robust predictive control strategy is proposed for the synchronization of fractional-order time-delay chaotic systems. A recurrent non-singleton type-2 fuzzy neural network (RNT2FNN) is used for the estimation of the unknown functions. Additionally, another RNT2FNN is used for the modeling of the tracking error. A nonlinear model-based predictive controller is then designed based on the proposed fuzzy model. The asymptotic stability of the approach is derived based on the Lyapunov stability theorem. A number of simulation examples are presented to verify the effectiveness of the proposed control method for the synchronization of two uncertain fractional-order time-delay identical and nonidentical chaotic systems. The proposed control strategy is also employed for high-performance position control of a hydraulic actuator. In this example, the nonlinear mechanical model of the hydraulic actuator, instead of a mathematical model, is simulated. The example demonstrates that the proposed control strategy can be applied to a wide class of nonlinear systems.