Stochastic Nonlinear Systems Control via Adaptive Fuzzy Integral Sliding Mode

This paper investigates adaptive integral sliding mode control (AISMC) for stochastic nonlinear systems based on Takagi–Sugeno (T–S) fuzzy modeling. To address this issue, an adaptive integral sliding mode control scheme is proposed. Specifically, adaptive parameter estimation is incorporated into the fuzzy controller to mitigate the conservative control performance and poor robustness associated with traditional fixed‐gain designs. Based on stochastic Lyapunov stability theory, it is proven that the trajectories of the closed‐loop system inevitably remain on the integral sliding surface. The stability of the sliding motion is verified via linear matrix inequalities. Finally, simulations of an inverted pendulum example demonstrate the superiority and effectiveness of the proposed method.