Fuzzy Sliding Mode Control of a Magnetic Ball Suspension System

This paper presents an adaptive fuzzy estimator sliding mode position control design for robust stabilization and disturbance rejection for a magnetic ball suspension system (MBSS). In general, the conventional sliding mode control design assumes that the upper boundary of the parameter variations and external disturbances is known and the sign function is used. It causes high frequency chattering and high gain phenomenon. In this paper, we propose a novel adaptive fuzzy estimator sliding mode control for the MBSS to avoid the high gain and reduce the chattering magnitude. The parameter variation and external disturbance estimator is designed to estimate the unknown lumped uncertainty values in real-time. This is different from the conventional fuzzy sliding mode control which estimates the unknown upper boundary uncertainty. This method utilizes a Lyapunov function candidate to guarantee convergence and asymptotically track the MBSS position commands. We employ experiments to validate the proposed method.