A Contraction-constrained Model Predictive Control for Multi-timescale Nonlinear Processes

2022/05/09 by Ryan McCloy, Lai Wei, McCloy, Ryan +3
Engineering · #Advanced Control Systems Optimization #FOS: Electrical engineering #FOS: Mathematics #Fuel Cells and Related Materials #Membrane Separation and Gas Transport #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2205.04465

openalex publication_date 2022/05/09 · openalex created_date 2022/05/22 · openalex updated_date 2026/07/28

Abstract

Many chemical processes exhibit diverse timescale dynamics with a strong coupling between timescale sensitive variables. Model predictive control with a non-uniformly spaced optimisation horizon is an effective approach to multi-timescale control and offers opportunities for reduced computational complexity. In such an approach the fast, moderate and slow dynamics can be included in the optimisation problem by implementing smaller time intervals earlier in the prediction horizon and increasingly larger intervals towards the end of the prediction. In this paper, a reference-flexible condition is developed based on the contraction theory to provide a stability guarantee for a nonlinear system under non-uniform prediction horizons.

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