Constrained Distributed Model Predictive Control for Linear Systems with Delayed Input

被引:0
|
作者
Zhang, Langwen [1 ,2 ]
Wang, Jingcheng [1 ,2 ]
Liu, Zhengfeng [1 ,2 ]
Li, Kang [3 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ China, Key Lab Syst Control & Informat, Shanghai 200240, Peoples R China
[3] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT7 1NN, Antrim, North Ireland
来源
2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年
基金
中国国家自然科学基金;
关键词
Constrained distributed model predictive control; delayed input; polytopic uncertain; LMI; POLYTOPIC UNCERTAIN SYSTEMS; MPC ALGORITHM; ROBUST MPC; SATURATION; SUBJECT; STATE;
D O I
暂无
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, an approach to design constrained distributed model predictive control (MPC) is proposed for the polytopic uncertain systems with input delays. The large-scale linear system we consider is decomposed into several subsystems with distributed control inputs. This allows us to design distributed MPC controller independently for each subsystem. An augmented polytopic uncertainty description is invoked to handle the input delays. At each time interval, each sub-controller solves a linear matrix inequality (LMI) optimization problem to obtain local control input. An iterative online algorithm for constrained distributed MPC is introduced to coordinate the distributed MPC controllers. A numerical example is simulated to demonstrate the effectiveness of the proposed algorithm.
引用
收藏
页码:4230 / 4235
页数:6
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