Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is t...Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.展开更多
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system comp...Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.展开更多
The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q le...The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.展开更多
随着碳中和目标的推进,综合能源系统(integrated energy system,IES)以其多能耦合、能量梯级利用等优势,逐渐成为能源供应的重要发展方向。在具有差异化用能需求的多功能区IES之间实现协同规划与调度,对提高系统经济性、降低系统碳排放...随着碳中和目标的推进,综合能源系统(integrated energy system,IES)以其多能耦合、能量梯级利用等优势,逐渐成为能源供应的重要发展方向。在具有差异化用能需求的多功能区IES之间实现协同规划与调度,对提高系统经济性、降低系统碳排放有着重要作用。然而,由于碳捕集机组、多类型氢能利用设备等低碳元件的接入以及可再生能源发电的不断增加,随之而来的元件模型非凸性与系统内多类型不确定性对系统规划的影响亟需研究。对此,该文考虑了机组低碳改造和氢能多模式利用低碳特性,提出了一种针对多功能区综合能源系统的不确定性协同规划方法。首先,详细分析了多功能区供/用能特性与多能互补关系,构建了具有分区差异化特征的多功能区设备规划策略。其次,建立了低碳改造后的热电联产机组和氢能多模式利用设备的数学模型,并对其低碳特性进行了分析。基于此,为应对规划周期内系统低碳改造成本的不确定性和短期内可再生能源出力的不确定性,提出了一种混合长-短期不确定性的多功能区IES协同规划模型。通过基于二进制扩展的凸包线性化方法,对所提规划模型中的非线性约束进行凸化,并采用相应的迭代收缩求解算法实现模型的有效求解。最后,通过某实际多功能区IES算例进行仿真,结果验证了所提模型和所用算法的有效性。展开更多
文摘Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.
基金Projects(61071096,61003233,61073103)supported by the National Natural Science Foundation of ChinaProjects(20100162110012,20110162110042)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.
基金supported by the National Natural Science Foundation of China(60874040)
文摘The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.
文摘随着碳中和目标的推进,综合能源系统(integrated energy system,IES)以其多能耦合、能量梯级利用等优势,逐渐成为能源供应的重要发展方向。在具有差异化用能需求的多功能区IES之间实现协同规划与调度,对提高系统经济性、降低系统碳排放有着重要作用。然而,由于碳捕集机组、多类型氢能利用设备等低碳元件的接入以及可再生能源发电的不断增加,随之而来的元件模型非凸性与系统内多类型不确定性对系统规划的影响亟需研究。对此,该文考虑了机组低碳改造和氢能多模式利用低碳特性,提出了一种针对多功能区综合能源系统的不确定性协同规划方法。首先,详细分析了多功能区供/用能特性与多能互补关系,构建了具有分区差异化特征的多功能区设备规划策略。其次,建立了低碳改造后的热电联产机组和氢能多模式利用设备的数学模型,并对其低碳特性进行了分析。基于此,为应对规划周期内系统低碳改造成本的不确定性和短期内可再生能源出力的不确定性,提出了一种混合长-短期不确定性的多功能区IES协同规划模型。通过基于二进制扩展的凸包线性化方法,对所提规划模型中的非线性约束进行凸化,并采用相应的迭代收缩求解算法实现模型的有效求解。最后,通过某实际多功能区IES算例进行仿真,结果验证了所提模型和所用算法的有效性。
