EXPERIMENTAL VERIFICATION OF STABILIZING SPLINE-BASED CONTINUOUS-TIME MODEL PREDICTIVE CONTROL SCHEME WITH ADAPTATION OF TERMINAL SET

Abstract In this paper a continuous-time Model-based Predictive Control (MPC) problem is approached in a sub-optimal way utilizing polynomial spline functions as the plant control input signals and B-splines for approximation of the continuous-time performance index. The optimization is performed with respect to a sequence of spline coefficients belonging to predicted control input profiles. The suggested solution enables us a continuous-time satisfaction of the plant signal constraints. Closed-loop stability is ensured through infinite horizon formulation by means of a terminal cost, a terminal constraint set, and a local controller. The presented scheme is applied on-line, supporting adaptation of the terminal set and resulting algorithm. The efficacy of the approach is illustrated through an experimental verification on a laboratory scale system.