Sliding mode control of fractional order chaotic system based on an online error correction adaptive SVR

Abstract

In this paper, a sliding mode control based on an online error correction adaptive SVR is put forward for a class of fractional order chaotic system with nonlinear uncertainty. In order to solve the problem that the uncertainty of the fractional order chaotic system model is difficult to predict, so the nonlinear function of the system is estimated by the offline SVR and the state trace error is forecasted by using incremental learning adaptive online SVR. In addition, the adaptive parameter adjustment law is selected by using the Lyapunov stability theory. Result of simulation of the fractional order Arneodo system shows that the sliding mode control based on the online error correction adaptive SVR can stabilize the nonlinear uncertain fractional order chaotic system with external noise disturbance to an expected state within a limited time. At the same time, both the control performance and the prediction precision of the system's nonlinear function can be improved.