动态博弈框架下的分布式动态优化
Distributed dynamic optimization in the framework of dynamic games
摘要点击 92  全文点击 165  投稿时间:2019-04-26  修订日期:2019-10-21
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DOI编号  10.7641/CTA.2019.90296
  2020,37(6):1185-1195
中文关键词  滚动时域优化  分布式动态优化  动态博弈  系统稳定性  化工过程网络
英文关键词  receding horizon optimization  distributed dynamic optimization  dynamic game  system stability  chemical process network
基金项目  国家自然科学基金项目(61773341), 国家重点实验室自主课题项目(ICT1804)资助.
作者单位E-mail
朱强 浙江大学控制科学与工程学院 568414010@qq.com 
王可心 浙江大学控制科学与工程学院  
邵之江 浙江大学控制科学与工程学院  
中文摘要
      为了实时在线求解复杂的大规模动态优化问题, 本文基于动态博弈理论提出了一种分布式动态优化方案, 滚动合作博弈优化(RCGO). 首先基于滚动时域优化框架, 该方案将原本复杂的大规模动态优化问题分解为若干简 单的小规模局部优化子问题, 使得计算复杂度降低从而保证优化求解的实时性. 之后本文基于动态博弈提出了分 解迭代法求解各局部动态优化子问题, 并对RCGO优化方案下系统稳定性进行分析. 最后本文选择一个化工过程网 络作为仿真案例, 基于RCGO方案得到了极大化经济效益下该网络的最优操作. 优化结果表明在求解复杂大规模动 态优化问题时, RCGO方案较传统的集中式优化方案在由系统经济效益、闭环控制性能及优化求解实时性等组成的 综合指标上有较大优势.
英文摘要
      In order to solve complex large-scale dynamic optimization problems online and in real time, this paper proposes a distributed dynamic optimization scheme called receding cooperative game optimization (RCGO) based on dynamic games. Firstly, based on the receding horizon optimization framework, the scheme decomposes original complex large-scale dynamic optimization problems into several simple small-scale local dynamic optimization subproblems, which reduces the computational complexity and ensures the real-time solutions of the dynamic optimization problems. Then, based on dynamic games, the iterative decomposition method is proposed to solve local dynamic optimization subproblems, and the system stability under the RCGO scheme is analyzed. Finally, this paper uses a chemical process network as a simulation case. Based on the RCGO scheme, the optimal operations of the network with the maximum economic benefit are obtained. The optimization results show that when solving complex large-scale dynamic optimization problems online, the RCGO has more advantages than the traditional centralized dynamic optimization scheme in terms of the system economic benefit, closed-loop control performance and real-time optimization solution.