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

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, paper proposes an enhanced unknown dynamics estimator (USDE)-based sliding mode (USDE-SMC) method a novel predictive-adaptive switching (PAS) controller (USDE-SMC-PAS). First, USDE incorporated into SMC to compensate for uncertainties, including disturbance, parametric uncertainty, model mismatch nonlinearities; second, adaptive (AS) used reduce chattering; finally, modified PAS enhance dynamic response ability uncertainty rejection with reduced chattering. In controller, gain comprises filtered estimation error part residual part, which are obtained first-order filter law, respectively. Consequently, strong nonlinearity compensation ability, high levitation accuracy, response, chattering property can be achieved simultaneously. stability properties USDE-SMC, USDE-SMC AS (USDE-SMC-AS), USDE-SMC-PAS in closed-loop investigated Lyapunov theorem. Simulations experiments provided validate effectiveness superior proposed method.