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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!

Model Predictive Control (MPC) Unit 1 Distributed Control System (PID) Unit 2 Distributed Control System (PID) FC PC TC LC FC PC TC LC Unit 2 - MPC Structure. Example: Blending System • Control rA and rB • Control q if possible •Flowratesof additives are limited Classical Solution MPC: Solve at

  Model, Predictive, Predictive models

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