(340i) Multi-Objective and Hierarchical Explicit Model Predictive Control
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Control
Friday, November 20, 2020 - 8:00am to 9:00am
This work proposes solution methods for both MOMPC and HMPC using multiparametric programming. Assuming that there exist two or (possibly) more conflicting control objectives described by linear or multiple convex quadratic functions, we develop multiparametric-based approaches for the derivation of the explicit Pareto front of MOMPC, and the explicit solution of HMPC. The MOMPC problem is reformulated into a multiparametric programming problem, which can then be exactly solved using state-of-the-art algorithms [8,9], while the HMPC problem is reformulated into a multiparametric multi-level programming problem, which can be exactly solved using the algorithm proposed in [10]. A case study on a chemostat with two competing objectives, an economic and a tracking objective, is used to illustrate the developed control strategies and compare them against each other, but also against pure tracking and pure economic model predictive controllers. The results of this study clearly indicate the effect of the different control strategies on the operation of the chemostat.
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