Guaranteed Cost Approach to Robust Model Predictive Control of Uncertain Linear Systems

摘要

In this paper we propose a constrained guaranteed cost robust modelpredictive controller (GCMPC) for uncertain discrete time systems. Thiscontroller was developed based on a quadratic cost functional and guaranteerobustness with respect to quadratically bound uncertainties. Such a class ofproblems is currently intractable by Min-Max Robust Model PredictiveControllers without polytopic approximations of the uncertainties. The proposedtechnique is computationally more efficient then an enumeration-based approachand requires only a Quadratically Constrained Quadratic Problem (QCQP)optimization, whereas LMI-based GCMPC approaches require a Semi-DefiniteProgramming (SDP) optimization.