Abstract
AbstractThis work proposes a method, based on optimization, for tuning model–based predictive controllers. The optimized controller has to guarantee appropriated gain and phase margins, sensitivity functions and robustness specifications. The method will be illustrated on Generalized Predictive Control, GPC, and its fractional–order counterpart, FGPC. The method has been tested out and validated in a real time application, the control of a rail–vehicle.
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