Distributed non-cooperative robust MPC based on reduced-order models  

作　　者：Yushen LONG Shuai LIU Lihua XIE Karl Henrik JOHANSSON 

机构地区：[1]School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore [2]ACCESS Linnaeus Center, School of Electrical Engineering, Royal Institute of Technology, SE-100 44, Stockholm, Sweden

出　　处：《Control Theory and Technology》2016年第1期11-20,共10页控制理论与技术（英文版）

基　　金：This work was supported by the Republic of Singapore＇s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore （BEARS） for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics （SinBerBEST） Program. BEARS has been established by the UniversiW of California, Berkeley as a center for intellectual excellence in research and education in Singapore. This work was also supported by the National Natural Science Foundation of China （Nos. 61573220, 61304045）.

摘　　要：In this paper, a non-cooperative distributed MPC algorithm based on reduced order model is proposed to stabilize large-scale systems. The large-scale system consists of a group of interconnected subsystems. Each subsystem can be partitioned into two parts： measurable part, whose states can be directly measured by sensors, and the unmeasurable part. In the online computation phase, only the measurable dynamics of the corresponding subsystem and neighbour-to-neighbour communication are necessary for the local controller design. Satisfaction of the state constraints and the practical stability are guaranteed while the complexity of the optimization problem is reduced. Numerical examples are given to show the effectiveness of this algorithm.In this paper, a non-cooperative distributed MPC algorithm based on reduced order model is proposed to stabilize large-scale systems. The large-scale system consists of a group of interconnected subsystems. Each subsystem can be partitioned into two parts： measurable part, whose states can be directly measured by sensors, and the unmeasurable part. In the online computation phase, only the measurable dynamics of the corresponding subsystem and neighbour-to-neighbour communication are necessary for the local controller design. Satisfaction of the state constraints and the practical stability are guaranteed while the complexity of the optimization problem is reduced. Numerical examples are given to show the effectiveness of this algorithm.

关 键 词：Model predictive control distributed control building energy efficiency 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置] TP317[自动化与计算机技术—控制科学与工程]