Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics

被引：17

作者：

Zhao, Meng ^{[1
]}

Ding, Baocang ^{[1
]}

机构：

[1] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China

来源：

ISA TRANSACTIONS | 2015年 / 55卷

关键词：

Distributed control; Model predictive control (MPC); Compatibility condition; Exponentially stability; RECEDING HORIZON CONTROL; LINEAR-SYSTEMS; MPC; STABILITY; BENCHMARK; TRACKING;

D O I：

10.1016/j.isatra.2014.07.012

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. (C) 2014 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：1 / 12

页数：12

共 41 条

[21] Approximate explicit receding horizon control of constrained nonlinear systems [J].

Johansen, TA .

AUTOMATICA, 2004, 40 (02) :293-300

[22] Decentralized receding horizon control for large scale dynamically decoupled systems [J].

Keviczky, Tamas ;

Borrelli, Francesco ;

Balas, Gary J. .

AUTOMATICA, 2006, 42 (12) :2105-2115

[23] Exponential stability of constrained receding horizon control with terminal ellipsoid constraints [J].

Lee, JW .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (01) :83-88

[24] Nash-optimization enhanced distributed model predictive control applied to the Shell benchmark problem [J].

Li, SY ;

Zhang, Y ;

Zhu, QM .

INFORMATION SCIENCES, 2005, 170 (2-4) :329-349

[25] Iterative Distributed Model Predictive Control of Nonlinear Systems: Handling Asynchronous, Delayed Measurements [J].

Liu, Jinfeng ;

Chen, Xianzhong ;

de la Pena, David Munoz ;

Christofides, Panagiotis D. .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (02) :528-534

[26] Distributed Model Predictive Control of Nonlinear Systems Subject to Delayed Measurements [J].

Liu, Jinfeng ;

Munoz de la Pena, David ;

Christofides, Panagiotis D. .

PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, :7105-7112

[27] Distributed model predictive control of nonlinear systems subject to asynchronous and delayed measurements [J].

Liu, Jinfeng ;

Munoz de la Pena, David ;

Christofides, Panagiotis D. .

AUTOMATICA, 2010, 46 (01) :52-61

[28] Distributed Model Predictive Control of Nonlinear Process Systems [J].

Liu, Jinfeng ;

Munoz de la Pena, David ;

Christofides, Panagiotis D. .

AICHE JOURNAL, 2009, 55 (05) :1171-1184

[29]

Maestre J. M., 2009, JOINT 48 IEEE C DEC

[30] Stabilizing decentralized model predictive control of nonlinear systems [J].

Magni, L. ;

Scattolini, R. .

AUTOMATICA, 2006, 42 (07) :1231-1236

← 1 2 3 4 5 →