Predictive-adaptive sliding mode control method for reluctance actuator maglev system

Abstract

The control performance of the reluctance actuator maglev system is seriously affected by inherent nonlinearities (e.g. hysteresis, eddy current, flux leakage, etc.) and external disturbances. To this end, this paper proposes an enhanced unknown system dynamics estimator (USDE)-based sliding mode control (USDE-SMC) method by a novel predictive-adaptive switching (PAS) controller (USDE-SMC-PAS). First, a USDE is incorporated into SMC to compensate for the uncertainties, including the external disturbance, the parametric uncertainty, and the model mismatch of inherent nonlinearities; second, an adaptive switching (AS) controller is used to reduce chattering; finally, the switching controller is modified by PAS to enhance the dynamic response ability and uncertainty rejection ability with reduced chattering. In the PAS controller, the switching gain comprises a filtered estimation error part and a residual error part, which are obtained by a first-order filter and an adaptive law, respectively. Consequently, the strong nonlinearity and uncertainty compensation ability, high levitation accuracy, high dynamic response, and reduced chattering property can be achieved simultaneously. The stability properties of USDE-SMC, USDE-SMC with an AS controller (USDE-SMC-AS), and USDE-SMC-PAS in the closed-loop system are investigated by the Lyapunov theorem. Simulations and experiments are provided to validate the effectiveness and superior performance of the proposed method.