A primal-dual active-set method for distributed model predictive control

被引：15

作者：

Koehler, Sarah ^{[1
]}

Danielson, Claus ^{[1
]}

Borrelli, Francesco ^{[1
]}

机构：

[1] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA

来源：

OPTIMAL CONTROL APPLICATIONS & METHODS | 2017年 / 38卷 / 03期

基金：

美国国家科学基金会;

关键词：

control of constrained systems; networked control systems; distributed optimization; large-scale optimization problems and methods; ALGORITHM; SYSTEMS; OPTIMIZATION; PROGRAMS; ADMM;

D O I：

10.1002/oca.2262

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a novel distributed primal-dual active-set method for model predictive control. The primal-dual active-set method is used for solving model predictive control problems for large-scale systems with quadratic cost, linear dynamics, additive disturbance, and box constraints. The proposed algorithm is compared with dual decomposition and an alternating direction method of multipliers. Theoretical and experimental results show the effectiveness of the proposed approach for large-scale systems with communication delays. The application to building control systems is thoroughly investigated. Copyright (C) 2016 John Wiley & Sons, Ltd.

引用

页码：399 / 419

页数：21

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