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A Lecture on Model Predictive Control

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A Lecture on Model Predictive ControlJay H. LeeSchool of Chemical and Biomolecular EngineeringCenter for Process Systems EngineeringGeorgia Inst. of TechnologyPrepared for Pan American Advanced Studies Institute Program on Process Systems EngineeringSchedule Lecture 1: Introduction to MPC Lecture 2: Details of MPC Algorithm and Theory Lecture 3: Linear Model IdentificationLecture 1Introduction to MPC- Motivation- History and status of industrial use of MPC- Overview of commercial packagesKey Elements of MPC Formulation of the Control problem as an (deterministic) optimization problem On-line optimization Receding horizon implementation (with feedback update)()()),(0,,min10iiiiiipiiiiuuxFxux guxi= += Repeat!

Local Optimization • A separate steady-state optimization to determine steady-state targets for the inputs and outputs; RMPCT introduced a dynamic optimizer recently • Linear Program (LP) for SS optimization; the LP is used to enforce input and output constraints and determine optimal input and output targets for the thin and fat plant cases

  Model, Control, Dynamics, Predictive, Optimization, Model predictive control

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