| 基于多智能体模型的动车组分布式预测控制 |
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| 引用本文： | 李中奇, 杨辉, 张坤鹏, 付雅婷. 基于多智能体模型的动车组分布式预测控制. 自动化学报, 2014, 40(11): 2625-2631. doi: 10.3724/SP.J.1004.2014.02625 |
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| 作者姓名： | 李中奇 杨辉 张坤鹏 付雅婷 |
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| 作者单位： | 1.南昌大学机电工程学院 南昌 330031;;;2.华东交通大学电气与电子工程学院 南昌 330013;;;3.江西省先进控制与优化重点实验室 南昌 330013 |
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| 基金项目： | National Natural Science Foundation of China，the Key Program of China Min-istry of Railway，Natural Science Foundation of Jiangxi Province |
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| 摘 要： | 以高速铁路普遍采用的动力分散式动车组为研究对象.针对动车组由若干动力单元相互耦合组成的结构特点,以各动力单元为智能体.结合动车组牵引特性曲线和实际运行数据,应用减法聚类和模式分类算法建立各智能体多模型集.依据各智能体网络拓扑结构和相互耦合约束关系,建立动车组多智能体模型.针对各智能体的耦合约束,采用PID和GPC相结合的平稳起动切换控制策略和基于邻域优化的多智能体分布式协调控制算法,实现各智能体对给定速度的同步跟踪.基于CRH380A型动车组运行数据的仿真结果验证了本文方法的有效性.
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| 关 键 词： | 动车组 多智能体 非线性 多模型 分布式预测控制 同步跟踪 |
| 收稿时间： | 2013-06-17 |
| 修稿时间： | 2013-11-12 |
Distributed Mo del Predictive Control Based on Multi-agent Mo del for Electric Multiple Units |
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| LI Zhong-Qi, YANG Hui, ZHANG Kun-Peng, FU Ya-Ting. Distributed Model Predictive Control Based on Multi-agent Model for Electric Multiple Units. ACTA AUTOMATICA SINICA, 2014, 40(11): 2625-2631. doi: 10.3724/SP.J.1004.2014.02625 |
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| Authors: | LI Zhong-Qi YANG Hui ZHANG Kun-Peng FU Ya-Ting |
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| Affiliation: | 1. School of Mechanical and Electrical Engineer, Nanchang University, Nanchang 330031, China;;;2. School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang 330013, China;;;3. Key Laboratory of Advanced Control and Optimization of Jiangxi Province, Nanchang 330013, China |
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| Abstract: | The distributed-power electric multiple units (EMUs) are widely used in high-speed railway. Due to the structural characteristic of mutual-coupled power units in EMUs, each power unit is set as an agent. Combining with the traction/brake characteristic curve and running data of EMUs, a subtractive clustering method and pattern classification algorithm are adopted to set up a multi-model set for every agent. Then, the multi-agent model is established according to the multi-agent network topology and mutual-coupled constraint relations. Finally, we adopt a smooth start switching control strategy and a multi-agent distributed coordination control algorithm to ensure the synchronous speed tracking control of each agent. Simulation results on the actual CRH380A running data show the effectiveness of the proposed approach. |
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| Keywords: | Electric multiple units (EMUs) multi-agent nonlinear multi-models distributed model predictive control syn-chronous tracking |
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