In this paper the problem of assuring nominal stability in constrained predictive control is addressed for the case when, due to disturbances, inadequate constraints, etc., the reference cannot be reached within the p...
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In this paper the problem of assuring nominal stability in constrained predictive control is addressed for the case when, due to disturbances, inadequate constraints, etc., the reference cannot be reached within the prediction horizon. The proposed algorithm is formulated in the delta domain, but the idea can be extended to other kind of models. It combines the cancellation of modes at the end of the prediction horizon with a minimization of the distance to the controller reference. In this way, it assures stability even with open loop unstable processes while, at the same time, avoids the feasibility problems.
In this paper a procedure is presented to compute, at each sampling time, optimal future value of the controlled variables that can be effectively reached by the process in a given time horizon, taking into account th...
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In this paper a procedure is presented to compute, at each sampling time, optimal future value of the controlled variables that can be effectively reached by the process in a given time horizon, taking into account the process dynamics and constraints on inputs and outputs. The optimality is considered in relation to an economic index involving the process variables. These values of the controlled variables are taken as the desired optimum set points, applying a rolling horizon policy. To illustrate the behaviour the system, an application example with a two-inputs, three outputs simulated non-linear chemical reactor is presented.
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