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.
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页码：1 / 12
页数：12
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