A stabilizing cooperative-distributed gradient-based economic model predictive control strategy for constrained linear systems. (April 2022)

• Record Type: Journal Article
• Authors: Santana, Daniel D.; Odloak, Darci; Santos, Tito L.M.; Martins, Márcio A.F.
• Is Part Of: Journal of process control. Volume 112(2022)
• Page Start: 36
• Page End: 48
• Publication Date: 2022-04
• Subjects: Distributed model predictive control -- Economic model predictive control -- Optimizing control -- Target calculation -- Cooperative optimization; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.02.006
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: This paper proposes a stabilizing distributed gradient-based economic MPC strategy for cooperative control of constrained linear systems. This strategy is based on quadratic programming to limit the computational cost, and one key feature is the evaluation of an economically optimal steady-state directly in the control law, leading the closed-loop system towards it. The control law includes three ingredients to enlarge its domain of attraction and potentially avoid feasibility problems, namely: artificial steady-state, slack variables, and terminal equality constraints solely on non-stable states. A four-tank system is used to address the properties of the formulation, especially its stability in the nominal case, the capacity to track the desired target for a nonlinear performance economic function, and tackle unmeasured and persistent unmeasured disturbances. Highlights: Quadratic programming-oriented distributed economic MPC. Improved feasibility of the MPC control law through slacked terminal constraints. Enlargement of the domain of attraction through slacked terminal constraints. Economically optimal steady-state computed directly in the control law.