Journal of Shanghai Jiao Tong University ›› 2021, Vol. 55 ›› Issue (11): 1362-1370.doi: 10.16183/j.cnki.jsjtu.2020.342

Special Issue: 《上海交通大学学报》2021年“航空航天科学技术”专题 《上海交通大学学报》2021年12期专题汇总专辑

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Cooperative Control of Aircraft Ground Deicing Resources

LI Biao1,2, WANG Liwen1(), XING Zhiwei2, WANG Sibo2, LUO Qian3   

  1. 1. College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
    2. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
    3. Engineering Technology Research Center, The Second Research Institute of Civil Aviation Administration of China, Chengdu 610041, China
  • Received:2020-10-21 Online:2021-11-28 Published:2021-12-03
  • Contact: WANG Liwen


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.

Key words: air transportation, collaborative control, multi-Agent negotiation, model predictive control, ground deicing resources

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