Distributed model predictive control for continuous‐time nonlinear systems based on suboptimal ADMM. (31st August 2018)

• Record Type: Journal Article
• Authors: Bestler, Anja; Graichen, Knut
• Is Part Of: Optimal control applications and methods. Volume 40:Number 1(2019)
• Page Start: 1
• Page End: 23
• Publication Date: 2018-08-31
• Subjects: alternating direction multiplier method -- distributed model predictive control -- networked systems -- nonlinear systems -- stability -- suboptimality; Control theory -- Periodicals; Mathematical optimization -- Periodicals; 629.8312
• DOI: 10.1002/oca.2459
• Languages: English
• ISSNs: 0143-2087

Abstract

Summary: This paper presents a distributed model predictive control (DMPC) scheme for continuous‐time nonlinear systems based on the alternating direction method of multipliers (ADMM). A stopping criterion in the ADMM algorithm limits the iterations and therefore the required communication effort during the DMPC solution at the expense of a suboptimal solution. Stability results are presented for the suboptimal DMPC scheme under two different ADMM convergence assumptions. In particular, it is shown that the required iterations in each ADMM step are bounded, which is also confirmed in simulation studies.