飞机地面除冰资源协同控制  

Cooperative Control of Aircraft Ground Deicing Resources

作　　者：李彪 王立文 邢志伟 王思博 罗谦[3] LI Biao;WANG Liwen;XING Zhiwei;WANG Sibo;LUO Qian(College of Aeronautical Engineering,Civil Aviation University of China,Tianjin 300300,China;College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China;Engineering Technology Research Center,The Second Research Institute of Civil Aviation Administration of China,Chengdu 610041,China)

机构地区：[1]中国民航大学航空工程学院,天津300300 [2]中国民航大学电子信息与自动化学院,天津300300 [3]中国民用航空局第二研究所工程技术研究中心,成都610041

出　　处：《上海交通大学学报》2021年第11期1362-1370,共9页Journal of Shanghai Jiaotong University

基　　金：国家重点研发计划(2018YFB1601200);中央高校基本科研业务费中国民航大学专项项目(3122019094);中国民航大学研究生科研创新项目(205014060219);天津市研究生科研创新项目(2020YJSB098)。

摘　　要：针对多并行除冰任务下分布式资源协同能力较弱及均衡性低的问题,结合机场除冰资源配置及时空分布状态,提出了一种基于多Agent协商的飞机地面除冰资源协同控制方法.建立了多Agent除冰资源协同运行框架,设计了面向全局协同联合体招投标机制的资源优化方法,提升了整体任务均衡性.在协同运行方案的基础上构建自治多Agent协同优化模型,采用加入决策因子的模型预测控制方法生成自治协同控制策略,并面向实际场景验证所提方法的可行性.结果表明,基于优化方案生成的初始化协同控制策略容错时间均值达4.89 min,与其他传统方法相比,平均起飞容限最大提升1.015 min,平均利用率增加15.28%,保证了除冰资源的安全性及协同性.Aimed at the problem of weak coordination and low balance of distributed resources under multiple parallel deicing tasks,a cooperative control method of aircraft ground deicing resources based on multi-agent negotiation was proposed,which combined airport deicing resource allocation and space-time distribution.A framework for collaborative operation of multi-agent deicing resources was established,and a resource optimization method for the bidding mechanism of a global collaborative consortium was designed to improve the overall task balance.Based on the operating plan,an autonomous multi-agent resource collaborative optimization model was constructed.The model predictive control method was applied to generate a collaborative control strategy,and the feasibility was verified in actual scenarios.The results demonstrate that the resource coordination and anti-interference ability of the proposed method are significantly enhanced while meeting the real-time requirements.Compared with the results obtained by other methods,the average takeoff tolerance is 4.89 min,increased by 1.015 min,and the average utilization rate is increased by 15.28%,which can ensure the safety and synergy of deicing resources.

关 键 词：航空运输 协同控制 多AGENT协商 模型预测控制 地面除冰资源 

分 类 号：V351.392[航空宇航科学与技术—人机与环境工程] U8[交通运输工程]