A contraction-constrained economic Model Predictive Control for nonlinear processes using multi-timescale models. (February 2023)

• Record Type: Journal Article
• Authors: McCloy, Ryan; Wei, Lai; Bao, Jie
• Is Part Of: Journal of process control. Volume 122(2023)
• Page Start: 199
• Page End: 207
• Publication Date: 2023-02
• Subjects: Multi-timescales -- Nonlinear Model Predictive Control -- Discrete-time nonlinear systems -- Contraction theory; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2023.01.001
• Languages: English
• ISSNs: 0959-1524

Abstract

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, dynamics with different timescales can be included in an optimisation problem by implementing faster timescale models (with shorter time intervals) earlier in the prediction horizon and increasingly slower timescale models (with longer time intervals) towards the end. In this paper, a reference-flexible condition is developed based on contraction theory to provide a stability guarantee for cost minimising control of multiple timescale nonlinear systems using multiple predictive models. Highlights: A novel reference-flexible EMPC is developed for multi-timescale nonlinear systems. A modular contraction-based stability constraint is derived for EMPC. Timescale-specific control contraction metrics are developed. The contraction conditions are based on multi-timescale models.