Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems
This paper considers a class of large-scale systems which is composed of many interacting subsystems, and each of them is controlled by an individual controller. For this type of system, to improve the optimization performance of the entire closed-loop system in a distributed framework without the e...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-05-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2227-7390/6/5/86 |
| _version_ | 1811301720546869248 |
|---|---|
| author | Shan Gao Yi Zheng Shaoyuan Li |
| author_facet | Shan Gao Yi Zheng Shaoyuan Li |
| author_sort | Shan Gao |
| collection | DOAJ |
| description | This paper considers a class of large-scale systems which is composed of many interacting subsystems, and each of them is controlled by an individual controller. For this type of system, to improve the optimization performance of the entire closed-loop system in a distributed framework without the entire system’s information or too-complicated network information, connectivity is always an important topic. To achieve this purpose, a distributed model predictive control (DMPC) design method is proposed in this paper, where each local model predictive control (MPC) considers the optimization performance of its strong coupling subsystems and communicates with them. A method to determine the strength of the coupling relationship based on the closed-loop system’s performance and subsystem network connectivity is proposed for the selection of each subsystem’s neighbors. Finally, through integrating the steady-state calculation, the designed DMPC is able to guarantee the recursive feasibility and asymptotic stability of the closed-loop system in the cases of both tracking set point and stabilizing system to zeroes. Simulation results show the efficiency of the proposed DMPC. |
| first_indexed | 2024-04-13T07:15:00Z |
| format | Article |
| id | doaj.art-e4c17ea9d10746278f79a9e6a4ab5a32 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-04-13T07:15:00Z |
| publishDate | 2018-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-e4c17ea9d10746278f79a9e6a4ab5a322022-12-22T02:56:47ZengMDPI AGMathematics2227-73902018-05-01658610.3390/math6050086math6050086Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control SystemsShan Gao0Yi Zheng1Shaoyuan Li2Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaThis paper considers a class of large-scale systems which is composed of many interacting subsystems, and each of them is controlled by an individual controller. For this type of system, to improve the optimization performance of the entire closed-loop system in a distributed framework without the entire system’s information or too-complicated network information, connectivity is always an important topic. To achieve this purpose, a distributed model predictive control (DMPC) design method is proposed in this paper, where each local model predictive control (MPC) considers the optimization performance of its strong coupling subsystems and communicates with them. A method to determine the strength of the coupling relationship based on the closed-loop system’s performance and subsystem network connectivity is proposed for the selection of each subsystem’s neighbors. Finally, through integrating the steady-state calculation, the designed DMPC is able to guarantee the recursive feasibility and asymptotic stability of the closed-loop system in the cases of both tracking set point and stabilizing system to zeroes. Simulation results show the efficiency of the proposed DMPC.http://www.mdpi.com/2227-7390/6/5/86model predictive controldistributed model predictive controllarge-scale systemsneighborhood optimization |
| spellingShingle | Shan Gao Yi Zheng Shaoyuan Li Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems Mathematics model predictive control distributed model predictive control large-scale systems neighborhood optimization |
| title | Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems |
| title_full | Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems |
| title_fullStr | Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems |
| title_full_unstemmed | Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems |
| title_short | Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems |
| title_sort | enhancing strong neighbor based optimization for distributed model predictive control systems |
| topic | model predictive control distributed model predictive control large-scale systems neighborhood optimization |
| url | http://www.mdpi.com/2227-7390/6/5/86 |
| work_keys_str_mv | AT shangao enhancingstrongneighborbasedoptimizationfordistributedmodelpredictivecontrolsystems AT yizheng enhancingstrongneighborbasedoptimizationfordistributedmodelpredictivecontrolsystems AT shaoyuanli enhancingstrongneighborbasedoptimizationfordistributedmodelpredictivecontrolsystems |