| 基于滚动时域的无人机空战决策专家系统 |
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| 引用本文： | 傅莉,谢福怀,孟光磊,王东政. 基于滚动时域的无人机空战决策专家系统[J]. 北京航空航天大学学报, 2015, 41(11): 1994-1999. DOI: 10.13700/j.bh.1001-5965.2014.0726 |
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| 作者姓名： | 傅莉 谢福怀 孟光磊 王东政 |
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| 作者单位： | 1.沈阳航空航天大学航空航天工程学部, 沈阳 110136 |
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| 基金项目： | 国家自然科学基金，航空科学基金 |
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| 摘 要： | 针对专家系统法在空战应用中存在适应性差的缺陷,提出了一种基于滚动时域控制(RHC)的机动决策算法对空战机动决策专家系统进行改进.首先,系统地分析了在专家系统空战机动决策中的最优控制问题,完成了机动决策最优控制模型系统状态方程的建立、控制约束的设计以及指标函数的建立.在此基础上,根据滚动时域法原理,将整个空战过程分解为若干有限时域,并在每个时域内将空战机动决策问题视为初始条件不断更新的专家系统机动决策最优控制模型的求解,反复进行直到空战结束.仿真结果表明,在专家系统法失效的情况下,通过求解专家系统空战机动决策滚动时域最优控制模型,无人机能够快速地进行有效的机动决策.
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| 关 键 词： | 滚动时域控制(RHC) 最优控制模型 机动决策 专家系统 空战 |
| 收稿时间： | 2014-11-19 |
An UAV air-combat decision expert system based on receding horizon control |
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| FU Li,XIE Fuhuai,MENG Guanglei,WANG Dongzheng. An UAV air-combat decision expert system based on receding horizon control[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(11): 1994-1999. DOI: 10.13700/j.bh.1001-5965.2014.0726 |
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| Authors: | FU Li XIE Fuhuai MENG Guanglei WANG Dongzheng |
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| Affiliation: | 1.Faculty of Aerospace Engineering, Shenyang Aerospace University, Shenyang 110136, China2. School of Automation, Shenyang Aerospace University, Shenyang 110136, China3. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China |
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| Abstract: | Aiming at the poor adaptability of expert system in air combat, a maneuvering decision algorithm based on the receding horizon control (RHC) method was proposed to improve the air combat maneuvering decision-making expert system. Firstly, the optimal control problem was systematically analyzed in the air combat maneuvering decision-making expert system. The system state equation, the index function and the control constraints of the maneuvering decision-making optimal control model were established. On this basis, according to the principle of the RHC method, the whole air combat process was divided into some sequential ones with the finite time horizon. In each time horizon, the optimal control model of the maneuvering decision-making expert system was solved to conduct air combat maneuvering decisions with initial state updated. The process was repeated until the air combat was over. The simulation result shows that, through solving the RHC optimal control model of the air combat maneuvering decision-making expert system, the unmanned aerial vehicle (UAV) can rapidly take effective maneuvering decisions in the case of expert system failure. |
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| Keywords: | receding horizon control (RHC) optimal control model maneuvering decision expert system air combat |
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