| 引用本文: | 朱强,王可心,邵之江.动态博弈框架下的分布式动态优化[J].控制理论与应用,2020,37(6):1185~1195.[点击复制] |
| ZHU Qiang,WANG Ke-xin,SHAO Zhi-jiang.Distributed dynamic optimization in the framework of dynamic games[J].Control Theory and Technology,2020,37(6):1185~1195.[点击复制] |
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| 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 2071 全文点击 1132 投稿时间：2019-04-26 修订日期：2019-10-21 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 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. |
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| 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. |
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