Stabilizing Linear Mpc with Efficient Prioritized Infeasibility Handling
نویسندگان
چکیده
In order to minimize the number of situations when a model predictive controller fails to compute a control input, all practical MPC implementations should have a means to recover from infeasibility. We present a recently developed infeasibility handler which computes optimal relaxations of the relaxable constraints subject to a user-de ned prioritization. This infeasibility handler requires that only a single linear program needs to be solved on-line in addition to the standard quadratic programming problem. The method is illustrated on an example. Copyright 2000 IFAC
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