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由于平台之间信息和计算是高度分布的,平台的运动以及通信拓扑的变化,使得集中式协调控制结构很难实现。以最小通信量为基础的分散协同控制具有可扩展性、异构性和动态可重构性等特点,可靠性和鲁棒性较好。提出了集中和分散相结合的多平台协同控制系统结构,集中控制主要实施任务分配、通信管理以及编队管理,而平台之间则可在有限通信基础上实施分散化的局部规划、协调与控制,研究了多平台协同任务管理、规划与控制等主要关键技术。并以多平台协同多目标跟踪为例,研究了信息滤波与分散化信息融合算法,以多平台对目标感知总的互信息增量作为效能指标,实现了多平台多目标最优任务分配及多平台协同感知目标信息的极大化。
Due to the highly distributed information and computation between platforms, the movement of the platform and the change of the communication topology, it is very difficult to realize the centralized coordinated control structure. Decentralized collaborative control based on minimum traffic has the characteristics of scalability, heterogeneity and dynamic reconfigurability, and has good reliability and robustness. A centralized and decentralized multi-platform collaborative control system architecture is proposed. The centralized control mainly implements task assignment, communication management and formation management. Platform-based decentralized local planning, coordination and control can be implemented on the basis of limited communication. The key technologies of multi-platform collaborative task management, planning and control are studied. Taking the multi-platform cooperative multi-target tracking as an example, the information filtering and decentralized information fusion algorithm is studied. With the multi-platform, the incremental mutual information increment of target perception is taken as the performance index, and the multi-platform multi-objective optimal task allocation and multi Collaborative platform perceives the maximization of target information.