Adaptive sliding mode control for stabilization of stochastic chaotic systems with multi-constraints

This paper proposes an adaptive sliding mode control scheme for stabilization of two different stochastic chaotic systems with multi-constraints such as model uncertainties, disturbances, input nonlinearities and stochastic unknown parameters which are generated by the Wiener process. Using an adaptive control and a fuzzy logic systems, model uncertainties, disturbances and stochastic unknown parameters are estimated and applying only a low bound of input nonlinearity, input nonlinearity is handled. Based on Lyapunov stability theory, the proposed scheme can stabilize the stochastic chaotic systems and guarantee global stability of them. The simulation results show the effectiveness of the proposed scheme.