针对由多个相互关联微电网组成的多微电网系统的协调控制与能量优化管理问题，提出基于智能体协调的分布式预测控制算法。采用基于智能体协调的DMPC（Distributed Model Predictive Control）优化算法建立能量管理优化问题，协调多个微...针对由多个相互关联微电网组成的多微电网系统的协调控制与能量优化管理问题，提出基于智能体协调的分布式预测控制算法。采用基于智能体协调的DMPC（Distributed Model Predictive Control）优化算法建立能量管理优化问题，协调多个微电网系统以最小的操作成本实时、准确地向用户负荷提供需求质量的电能。并在各微电网系统的MPC优化问题设计时，只考虑各微电网系统的局部模型和状态信息，减小优化问题的复杂度并降低通信需求，提高系统优化的实时性。仿真结果表明，采用此优化方法，不仅能保证短期内用户负荷需求的实时跟踪，同时达到长期内能量的优化调度和电网的经济运行。展开更多
In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimi...In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimize average delay of arterial vehicles by training the interaction ability between agents and exterior environments. The Robertson platoon dispersion model is embedded in the RL algorithm to precisely predict platoon movements on arteries and then the reward function is developed based on the dispersion model and delay equations cited by HCM2000. The performance of the algorithm is evaluated in a Matlab environment and comparisons between the algorithm and the conventional coordination algorithm are conducted in three different traffic load scenarios. Results show that the proposed algorithm outperforms the conventional algorithm in all the scenarios. Moreover, with the increase in saturation degree, the performance is improved more significantly. The results verify the feasibility and efficiency of the established algorithm.展开更多
This paper reviews some main results and progress in distributed multi-agent coordination from a graph Laplacian perspective. Distributed multi-agent coordination has been a very active subject studied extensively by ...This paper reviews some main results and progress in distributed multi-agent coordination from a graph Laplacian perspective. Distributed multi-agent coordination has been a very active subject studied extensively by the systems and control community in last decades, including distributed consensus, formation control, sensor localization, distributed optimization, etc. The aim of this paper is to provide both a comprehensive survey of existing literature in distributed multi-agent coordination and a new perspective in terms of graph Laplacian to categorize the fundamental mechanisms for distributed coordination. For different types of graph Laplacians, we summarize their inherent coordination features and specific research issues. This paper also highlights several promising research directions along with some open problems that are deemed important for future study.展开更多
文摘针对由多个相互关联微电网组成的多微电网系统的协调控制与能量优化管理问题，提出基于智能体协调的分布式预测控制算法。采用基于智能体协调的DMPC（Distributed Model Predictive Control）优化算法建立能量管理优化问题，协调多个微电网系统以最小的操作成本实时、准确地向用户负荷提供需求质量的电能。并在各微电网系统的MPC优化问题设计时，只考虑各微电网系统的局部模型和状态信息，减小优化问题的复杂度并降低通信需求，提高系统优化的实时性。仿真结果表明，采用此优化方法，不仅能保证短期内用户负荷需求的实时跟踪，同时达到长期内能量的优化调度和电网的经济运行。
基金The National Key Technology R&D Program during the 11th Five-Year Plan Period of China (No. 2009BAG17B02)the National High Technology Research and Development Program of China (863 Program) (No. 2011AA110304)the National Natural Science Foundation of China (No. 50908100)
文摘In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimize average delay of arterial vehicles by training the interaction ability between agents and exterior environments. The Robertson platoon dispersion model is embedded in the RL algorithm to precisely predict platoon movements on arteries and then the reward function is developed based on the dispersion model and delay equations cited by HCM2000. The performance of the algorithm is evaluated in a Matlab environment and comparisons between the algorithm and the conventional coordination algorithm are conducted in three different traffic load scenarios. Results show that the proposed algorithm outperforms the conventional algorithm in all the scenarios. Moreover, with the increase in saturation degree, the performance is improved more significantly. The results verify the feasibility and efficiency of the established algorithm.
基金Project supported by the National Natural Science Foundation of China （No. 61273113）
文摘This paper reviews some main results and progress in distributed multi-agent coordination from a graph Laplacian perspective. Distributed multi-agent coordination has been a very active subject studied extensively by the systems and control community in last decades, including distributed consensus, formation control, sensor localization, distributed optimization, etc. The aim of this paper is to provide both a comprehensive survey of existing literature in distributed multi-agent coordination and a new perspective in terms of graph Laplacian to categorize the fundamental mechanisms for distributed coordination. For different types of graph Laplacians, we summarize their inherent coordination features and specific research issues. This paper also highlights several promising research directions along with some open problems that are deemed important for future study.
