Observer-based distributed model predictive control of complex systems with state coupling constraints

被引：3
|
作者：
Du, Shengli [1 ,2 ,3 ]
Cao, Boqi [1 ,2 ,3 ]
Li, Xu [4 ]
机构：
[1] Beijing Univ Technol, Sch Artificial Intelligence & Automat, Beijing 100124, Peoples R China
[2] Minist Educ, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing, Peoples R China
[3] Beijing Lab Smart Environm Protect, Beijing, Peoples R China
[4] Dalian Univ Technol, Key Lab Precis & Non Tradit Machining Technol Min, Dalian, Peoples R China
来源：
IET CONTROL THEORY AND APPLICATIONS | 2022年 / 16卷 / 13期
基金：
中国国家自然科学基金;
关键词：
LINEAR-SYSTEMS; MPC; COMMUNICATION; DECOMPOSITION; STABILITY; DESIGN;
D O I：
10.1049/cth2.12310
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the cooperative distributed model predictive control (DMPC) problem of a class of complex systems consisting of several subsystems is studied. The states of these subsystems are coupled with each other, and thus bring challenges for the model predictive control algorithm. Moreover, though the subsystems can communicate with each other, they only can access to the output information of their neighboring subsystems. In this case, Luenberger observers are used to estimate the unknown states and a distributed prediction strategy is established for the studied system. Then, the optimal control of the closed-loop system is realized by designing distributed model predictive controller on the basis of the estimated states. The terminal constraints are introduced in the proposed DMPC algorithm to ensure the iterative feasibility and also the stability of the closed-loop. Finally, the effectiveness of the proposed method is verified by a numerical simulation.
引用
收藏
页码：1364 / 1372
页数：9
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