Model Predictive Control of Chemical Processes: A Tutorial

In this chapter, we will illustrate the ability of model predictive control (MPC) in dealing with the multivariable nature of process dynamics, process constraints, and multiple control objectives in chemical processes. The mathematical formulation of MPC is presented for a general class of processes. The receding-horizon implementation of MPC is demonstrated for a batch crystallization process and a continuous fermentation process. We will then discuss the importance of state estimation for output-feedback MPC when the knowledge of the process states is not fully available. This chapter will conclude with a brief introduction to advanced topics in MPC that are of relevance to chemical process control.

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