信息与控制2018，Vol.47Issue(1)：1-4,4.DOI:10.13976/j.cnki.xk.2018.0001
网络化分布式CPS系统实时优化、 监控与安全控制
Real-time Optimization, Supervisory and Safety Control for Distributed Networked Cyber-physical System
摘要
Abstract
Networked CPS systems are a class of complicated physical systems with inter-connected and coupled sub-systems. By exchanging information via networks, each sub-system can coordinate and optimize their be-haviors and make local decisions in order to achieve global tasks. For this class of systems, it is difficult to solve the optimization problems efficiently and adaptively using the classical centralized approaches. There-fore, it is necessary and important to develop novel distributed optimization methods for networked systems. In particular, there is a great demand for such distributed methods in modern distributed networked systems, in-cluding smart-grids and sensor networks. In this project, we tackle the difficulties in real-time optimization and decision making of networked systems. By investigating the information exchange mechanisms and the physical couplings between each sub-system, three key problems are formulated:the constrained optimization problem when dynamical coupling, the decision making problem for consensus under multi-task conflict and the adaptive cooperation problem under network topology changes. By adjusting the feasible region of the dy-namically-coupled constrained optimization problem, analyzing and predicting the dynamic behavior of each sub-system, and switching the operation mode of the system, we develop a comprehensive framework for real-time optimization and decision making of networked systems. Much progress in the CPS optimization and control has been made, in this paper, some further problems are discussed based on the results of this special issue.关键词
信息物理融合系统/分布式实时优化/协同策略/自适应优化Key words
cyber-physical systems ( CPS)/distributed real-time optimization/coordination strategy/adaptive optimization分类
信息技术与安全科学引用本文复制引用
李少远,夏元清,程鹏..网络化分布式CPS系统实时优化、 监控与安全控制[J].信息与控制,2018,47(1):1-4,4.基金项目
国家自然科学基金资助项目(61590920) （61590920）
