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MPC provides the flexibility to act while optimizing, which is essential to the solution of many engineering problems in complex plants. This complete, step-by-step exploration of various approaches to MPC introduces basic concepts of systems, modeling, and predictive control - detailing development from classical MPC to synthesis approaches. It explores the use of Model Algorithmic Control (MAC), Dynamic Matrix Control (DMC), Generalized Predictive Control (GPC), and Two-Step Model Predictive Control and identifies important general approaches to synthesis. The book also discusses open-loop and closed-loop optimization in synthesis approaches and covers output feedback synthesis approaches with and without a finite switching horizon.
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