Observer-based indirect adaptive fuzzy integral sliding mode control with state variable filters

This paper proposes an observer-based indirect adaptive fuzzy integral sliding mode controller with state variable filters for a class of unknown nonlinear dynamic systems that not all the states are available for measurement. First, the fuzzy models for describing the input/output behavior of the nonlinear dynamic system are constructed. Next, an observer is applied to estimate the tracking error vector. Based on the observer, a fuzzy integral sliding model controller is developed for guaranteeing the tracking performance. Then, by passing the observation error vector to a set of state variable filters, a filtered observation error vector is obtained. With the filtered observation error vector, the adaptive laws for adjusting the free parameters of the fuzzy models can be designed. Finally, the stability of the overall system is analyzed based on the Lyapunov method. Simulation results demonstrate the tracking performance of the proposed controller.