Design and implementation of the adaptive estimator sliding mode controller for a magnetic ball suspension system

This paper presents an adaptive sliding mode position control design procedure 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. Therefore, it causes high frequency chattering and high gain phenomenon. In this paper, we propose an adaptive sliding mode control for the MBSS to avoid the above drawbacks. This method utilizes a Lyapunov function candidate to guarantee the convergence and asymptotically track the MBSS position commands. The estimator of parameter variations and external disturbances is designed to estimate the unknown lumped uncertainty values in real-time. This is different from the conventional adaptive sliding mode control which estimates the unknown upper boundary uncertainty. Finally, we employ the experiments to validate the proposed method.