Abstract
This paper is concerned with the application of sliding mode predictive control (SMPC) on a laboratory-scale magnetic levitation system. The main contribution consists of the use of multi-parametric programming to reduce the computational workload required for real-time implementation. For comparison, a conventional sliding mode controller was also employed. The task consisted of tracking a reference signal in the presence of control rate constraints. In this scenario, the sliding mode controller was not able to maintain closed-loop stability, whereas the SMPC controller successfully performed the tracking task, with proper satisfaction of the constraints.
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