Neural sliding mode control for magnetic levitation systems

Neural sliding mode control (NSMC) may decrease chattering of the sliding mode control (SMC) and improve control accuracy of the neural control (NC). There are some problems with the common parallel structure, such as the chattering is big at start stage. In order to overcome the above problem, we propose a new serial structure for NSMC, it is called two-stage neural sliding control. A dead-zone NC is used to make the tracking error bounded, then super-twisting second-order SMC is applied to guarantee finite time convergence. This new controllers has less chattering during its discrete realization, and ensures finite time convergence. Real-time experiments for a magnetic levitation system are presented to compare this new NSMC with regular controllers, such as PID, NC, SMC, and normal NSMC.