2019/07/23 by Yanxu Su, Yang Shi, Su, Yanxu +3
Chemistry · Engineering · #Advanced Control Systems Optimization #Control and Stability of Dynamical Systems #FOS: Mathematics #Fuel Cells and Related Materials #Metal-Organic Frameworks: Synthesis and Applications #Optimization and Control (math.OC)
paper · pdf · doi:10.48550/arxiv.1907.10169
openalex publication_date 2019/07/23 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28
This paper develops a distributed model predictive control (DMPC) strategy\nfor a class of discrete-time linear systems with consideration of globally\ncoupled constraints. The DMPC under study is based on the dual problem\nconcerning all subsystems, which is solved by means of the primal-dual gradient\noptimization in a distributed manner using Laplacian consensus. To reduce the\ncomputational burden, the constraint tightening method is utilized to provide a\ncapability of premature termination with guaranteeing the convergence of the\nDMPC optimization. The contraction theory is first adopted in the convergence\nanalysis of the primal-dual gradient optimization under discrete-time updating\ndynamics towards a nonlinear objective function. Under some reasonable\nassumptions, the recursive feasibility and stability of the closed-loop system\ncan be established under the inexact solution. A numerical simulation is given\nto verify the performance of the proposed strategy.\n