Model-Based Predictive Control
نویسنده
چکیده
MBPC is a feedback-control methodology suitable to enforce efficiently hard constraints on the variables of the controlled system. It is shown that the method hinges upon a constrained open-loop optimal control problem along with the adoption of the so-called receding-horizon control strategy. In the important case of time-invariant linear saturated ANCBI systems, MBPC algorithms can be devised with the property of ensuring global feasibility/stability. Considerations on how to deal with disturbances and model uncertainties are also given. A presentation of a simplified form of MBPC, viz. the PCG, is finally discussed.
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