Robust model predictive control of constrained linear systems

Linear matrix inequality (LMI) based optimization methods are applied to the problem of designing a model predictive controller for an uncertain constrained linear system. The control signal is specified in terms of both feedback and feedforward components, where the feedback is designed to maintain the state within a prescribed ellipse in the presence of unknown bounded disturbances and system perturbations. The feedforward component drives these ellipses to a desired reference state. The LMI characterization allows exact specification of ellipsoidal and hyperplane constraints on the inputs, states and outputs.

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