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机构地区:[1]中国科学院长春光学精密机械与物理研究所,吉林长春130033
出 处:《红外与激光工程》2015年第2期693-698,共6页Infrared and Laser Engineering
基 金:中国科学院知识创新工程国防科技创新重要项目(YYYJ-1122)
摘 要:无人机在光电侦察领域的应用越来越广泛,设计可靠的飞行控制器是完成侦察任务的必要手段。提出了一种基于模型匹配和遗传算法寻优的以非线性模型为被控对象的飞行控制器设计方法。通过该方法可以实现无人机飞行控制器与飞行仿真模型的一体化快速设计与仿真,与经典的飞行控制器设计方法相比,该方法能够比较快速、便捷地获得所需控制器。建立了包含气动、发动机和环境模型的某型无人机六自由度非线性全量数学模型,然后基于此模型,应用上述方法设计了无人机的飞行控制器,基于有限状态机理论建立了飞行管理模型,设计无人机飞行剖面并实现控制器切换,最后进行了六自由度非线性仿真,验证了所设计控制器的有效性。The application of UAV in the field of electro-optical reconnaissance is more and more widely. Desining a robust flight controller for UAV is an essential technique. A flight controller design method based on model matching and genetic algorithm optimization was proposed in this paper. A nonlinear model was used as the controlled object of this method. Compared with the classic flight controller design method, this method could access the needed controllers quickly and conveniently. A nonlinear mathematical six-degree-of-freedom model of a UAV was established, the aerodynamics, engine and environmental model were all included in this model. Using the above method, a UAV flight controller was designed. Based the finite state machine theory, the flight management model was established to design flight modes and carry out the controller switch. Finally, the six degrees of freedom nonlinear simulation was carried out to verify the effectiveness of the designed controller.
关 键 词:模型匹配 遗传算法 飞行控制 飞行仿真 有限状态机
分 类 号:TJ765.2[兵器科学与技术—武器系统与运用工程] V412[航空宇航科学与技术—航空宇航推进理论与工程]
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