Distributed MPC for linear discrete-time systems with disturbances and coupled states

This paper presents a robust non-iterative distributed model predictive control algorithm for spatially interconnected systems. The system consists of multiple linear discrete-time subsystems, which are weakly coupled in their states. Each subsystem is subject to state and input constraints as well...

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Bibliographic Details
Published in:	Systems & control letters Vol. 135; p. 104578
Main Authors:	Ma, Aoyun, Liu, Kun, Zhang, Qirui, Xia, Yuanqing
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.01.2020
Subjects:	Coupled states Distributed model predictive control Spatially interconnected systems State and input constraints Distributed model predictive control State and input constraints Spatially interconnected systems Coupled states
ISSN:	0167-6911, 1872-7956
Online Access:	Get full text
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Summary:	This paper presents a robust non-iterative distributed model predictive control algorithm for spatially interconnected systems. The system consists of multiple linear discrete-time subsystems, which are weakly coupled in their states. Each subsystem is subject to state and input constraints as well as disturbances. The predictive model of each subsystem updates its state, depending on its own state and the neighboring states. The disturbance and the model error are handled via robustness constraints. The recursive feasibility of the optimization problems and the stability of the closed-loop systems are established. Finally, the effectiveness and advantages of the proposed algorithm are verified via simulations.
ISSN:	0167-6911 1872-7956
DOI:	10.1016/j.sysconle.2019.104578