| 异构多无人机协同目标跟踪分散化最优控制 |
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| 引用本文： | 文元全,周锐,吴雯漫,孔繁峨.异构多无人机协同目标跟踪分散化最优控制[J].北京航空航天大学学报,2010,36(5):545-549. |
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| 作者姓名： | 文元全 周锐 吴雯漫 孔繁峨 |
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| 作者单位： | 大连海事大学,轮机工程学院,大连,116026;北京航空航天大学,自动化科学与电气工程学院,北京,100191;中国航空工业集团公司,洛阳电光设备研究所,洛阳,471009 |
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| 基金项目： | 国家自然科学基金，博士点基金资助项目，航空科学基金资助项目 |
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| 摘 要： | 针对主被动传感器协同目标跟踪需要,考虑到可扩展性、异构性和动态可重构性等特点,建立了适于不同测量类型和不同测量维数的异构多传感器分散化信息融合算法.以极大化信息融合所得到的信息熵及无人机(UAV,Unmanned Aerial Vehicles)观测信息质量为效能函数,建立了异构多UAV协同目标跟踪的分散化最优控制代价函数以及通信、防撞和控制等约束模型.实现了多UAV协同目标跟踪的分散化模型预测控制,并分析了通讯噪声等因素对分散化信息融合和协同控制的影响.
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| 关 键 词： | 目标跟踪 协同控制 信息融合 模型预测控制 无人机 |
| 收稿时间： | 2009-10-14 |
Decentralized optimal control of multiple heterogeneous UAVs in cooperative target tracking |
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| Wen Yuanquan,Zhou Rui,Wu Wenman,Kong Fane.Decentralized optimal control of multiple heterogeneous UAVs in cooperative target tracking[J].Journal of Beijing University of Aeronautics and Astronautics,2010,36(5):545-549. |
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| Authors: | Wen Yuanquan Zhou Rui Wu Wenman Kong Fane |
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| Institution: | Wen Yuanquan(Marine Engineering College,Dalian Maritime Universitiy,Dalian 116026,China)Zhou Rui Wu Wenman(School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100191,China)Kong Fan'e(Luoyang Institute of Optic-Electronic Equipment,China Aviation Industry Corporation,Luoyang 471009,China) |
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| Abstract: | The decentralized information fusion algorithms for multiple heterogeneous sensors platforms with different types and dimensions was developed to meet the needs of the target tracking with active and passive sensors. The decentralized information fusion algorithm was scalable, heterogeneous and reconfigurable. The performance cost function and constraints model of communication, collision avoiding and control for decentralized optimal control of multiple heterogeneous unmanned aerial vehicles(UAV) in cooperative target tracking were established to maximize the local information entropy obtained by information fusion and the quality of information observed by each UAV. The cooperative target tracking based on multiple heterogeneous UAV was implemented using decentralized model predictive control. The effects of imperfect communication on decentralized information fusion and cooperative control were investigated. |
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| Keywords: | target tracking cooperative control information fusion model predictive control unmanned aerial vehicles |
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