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摘要: 扑翼飞行器（Flapping-wing air vehicle，FAV）即通过模拟昆虫以及鸟类飞行方式而制造的仿生机器人.与常见的固定翼和旋翼飞行器相比，具有效率高、质量轻、机动性强、耗能低等显著优点，是飞行器发展的重要方向.关于扑翼机的研究始于上世纪后期，现如今从理论探索到机体开发都有了可喜的成果.本文首先介绍了世界领先的几款扑翼飞行器的特点，接着简述了扑翼飞行器在动力学、能源、控制等方面的发展现状，并对未来的研究方向做出了展望.Abstract: The flapping-wing air vehicle (FAV) is a sort of bionic-robot, which simulates insect and bird flight. Comparing with fixed and rotary-wing aircraft, FAV is characterized by efficiency, low mass, high flexibility and energy conservation, and is a major trend of the aircraft development. The study of FAV can date from the end of 20th century. And now, great achievements have been made both in the theoretical research and modeling. This overview introduces the characters of the leading FAVs in the world, followed by an overlook and outlook of the aerodynamics, energy-supply and control problem for FAVs.
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Key words:
- Flapping-wing air vehicle (FAV) /
- aerodynamics /
- fight control /
- flexible structure /
- vibration control
1) 本文责任编委 朱纪洪 -
图 13 南航仿鸟扑翼飞行器
Fig. 13 Bird-like FAV of Nanjing University of Aeronautics and Astronautics
表 1 扑翼机参数
Table 1 The parameters of FAV
名称 制作单位 质量(g) 翼展(cm) 推动频率(Hz) 飞行速度(m/s) 续航时间(s) Nano Hummingbird 航空环境公司 17.5 15.8 27.5 6.7 660 Phoenix 麻省理工学院 200 − 2.4 4 − Insect-scale 哈佛大学 0.08 3 120 0.3 20 SmartBird Festo 400 200 − − − Bat Bot UIUC 60 40 8 − − Ornithopter 亚利桑那大学 260 74 18 10 420 Microbat 加州理工大学 12.5 15.24 − 5 42 DelFly Delft 16 2.8 18 15 900 H2bird UC Berkeley 13 26.5 − 1.2 600 EPFL的扑翼机 EPFL 30 86 − 2.5 1 800 马里兰大学扑翼机 马里兰大学 425 107 5 8.3 150 ASN-211 西北工业大学 220 60 − 10 − 
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表 2 扑翼机控制方法优缺点比较
Table 2 The advantages and disadvantages of FAV control
控制分类 控制方法 优缺点 无模型主动控制 主动(被动)位置反馈[58] 优点: 1) 自适应性; 2) 有效抑制振动同时又不降低系统的稳定性.
缺点: 1) 频率不能时变; 2) 难以应对多种系统模型; 3) 形成高阶控制器.线性速度反馈[59] 优点:保证了闭环系统的无条件稳定性.
缺点: 1) 要求微分器实现; 2) 增加了全频段的控制难度.PID[60] 优点: 1) 结构简单; 2) 性能可靠; 3) 应用广泛.
缺点: 1) 不具有自适应性; 2) 不能应用于可调变化中.分数阶控制[61] 优点: 1) 对不同负载具有鲁棒性; 2) 可消除扰动的影响.
缺点:只能应用于常系数线性系统.奇摄动控制[62] 优点:能把复杂系统高阶项分成简单的低阶子系统.
缺点: 1) 当考虑高阶项时增加项的解将变得非常复杂;
2) 模型的不确定性将会反映在缓慢变化的动态性能中.无模型的被动控制 被动定理[63] 优点:简单且对于动态性能的变化具有鲁棒性.
缺点: 1) 动作控制反应慢; 2) 不够高效; 3) 对关节摩擦敏感.无模型主被动组合控制 内外环[64] 优点: 1) 暂态收敛速度快; 2) 具有准确的稳态跟踪率;
3) 可以消除一些扰动的影响; 4) 简化控制动作;
缺点:传感器和变送器增多.无模型自适应/智能控制 滑膜控制[65] 优点: 1) 可用于处理模型未知或者不确定系统;
2) 有效保持了系统的稳定性和一致性; 3) 降低阶次.
缺点:可能导致无模型系统的振动、能量损失、设备损坏.自适应控制[66] 优点:可以应对系统变负载和位置扰动.
缺点:自适应因子独立于过程, 需要额外调节.神经网络控制[67] 优点: 1) 能在系统动态性能未知的情况下很快建立控制器;
2) 有效应对数学描述错误的系统.
缺点: 1) 训练样本和离线学习很耗时且结算量庞大;
2) 训练样本少会导致系统性能差.模糊控制[68] 优点: 1) 不需要准确的物理模型或真实的物理系统; 2) 易于设计和应用;
3) 可以由非专门人员实现和执行; 4) 通过调节参数可以有效处理非线性.
缺点: 1) 对于没有经验的人, 很难选择合适的参数;
2) 如果系统的参数变化很大且没有规律, 那么控制效果将很差.基于模型的控制器设计 前馈控制[69] 优点:不需要传感器.
缺点: 1) 不适用于有扰、不确定和负载变化的系统; 2) 不能忽略非线性.系统优化[70] 优点:易于设计和操作.
缺点: 1) 对于非线性控制问题缺乏解析解; 2) 是个无限时间问题.边界控制[71] 优点: 1) 轨迹跟踪效果好; 2) 有效应对系统的扰动和振动.
缺点:难以处理参数不确定系统.预测控制[72] 优点: 1) 可以解决非最小相位系统的时延问题;
2) 有效处理反馈时延和非线性系统的约束问题;
3) 不用把系统分解成子系统却又良好的鲁棒性.
缺点:不能产生快速稳定的响应.
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