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.