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An Adaptive LPV MPC Formulation for Industrial Non-linear Processes

Abstract

This code presents the design of an adaptive Linear Parameter Varying Model Predictive Control (LPV-MPC) scheme for chemical industrial processes. The proposed LPV-MPC method resides in the operation of two consecutive Quadratic Programing (QP) problems: a Moving Horizon Estimator (MHE) and a regular Model Predictive Controller (MPC). The MPC includes a terminal set constraint to ensure recursive feasibility. The terminal set is determined offline through an Linear Matrix Inequalities (LMI) problem.

Simulation results, based on a Solar Thermal (ST) collector is given to illustrate the implementation and performance of such approach.

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Paper info

Bernardi, Emanuel, Hugo Pipino, Carlos A. Cappelletti, and Eduardo J. Adam. "Adaptive Predictive Control for Industrial Processes." In 2021 XIX Workshop on Information Processing and Control (RPIC), pp. 1-6. IEEE, 2021.

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Emanuel Bernardi

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Linear Parameter Varying Model Predictive Control

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