带有网络拓扑优化的分布式预测控制方法（英文）  

Distributed model predictive control with optimal network topology for large scale systems

作　　者：魏永松[1] 李少远[1] 

机构地区：[1]上海交通大学自动化系系统控制与信息处理教育部重点实验室,上海200240

出　　处：《控制理论与应用》2015年第9期1269-1276,共8页Control Theory & Applications

基　　金：Supported by National Nature Science Foundation of China(61233004,61221003);National Basic Research Program of China(973 Program-2013CB035500)

摘　　要：通常在大系统中,全局信息优化的系统,其性能要高于局部信息优化系统.全局信息优化的算法由于大系统的复杂程度往往不可行.所以通常会用分布式算法来解决此类问题.在分布式算法中,为了获得更好的系统性能,要尽可能多的采用更多的信息信息交换,然而这样会带来信息网络的负担增大.本文在预测控制性能指标中引入通信代价,并提出了一种随着系统状态变化的通信网络拓扑切换方法.文中给出了该算法在供水管网动态模型中的仿真结果,表明本方法的可行性.Generally,the performance of a large-scale system in global optimization is better than that in local optimization.To obtain a better performance,we need more information interchanges.However,in a distributed model prediction algorithm,this will increase the workload for an information network,making global optimization inapplicable in a large-scale system with complexity.To deal with this problem,we introduce the communication cost in the performance index and develop a novel method for switching the communication-network topology according to variations in system states.This method has been applied to the simulation experiment of a dynamical model of a water supply network system,demonstrating the feasibility of the proposed algorithm.

关 键 词：分布式系统 预测控制 拓扑优化 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]