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摘要: 微型扑翼飞行器(Flapping wing micro aerial vehicle, FWMAV)因飞行效率高、质量轻、耗能低、机动性强等显著优点, 在飞行器研究和应用中占据重要地位. 目前, FWMAV姿态控制成为飞行器控制研究领域的研究热点. 针对FWMAV姿态控制问题, 基于平行智能理论框架提出了一种FWMAV抗扰动姿态控制器. 通过建立人工系统(Artificial systems, A)、计算实验(Computational experiments, C)、平行执行(Parallel execution, P)三个过程, 得到一个能够有效解决FWMAV姿态控制过程中扰动问题的控制器, 并通过理论分析和数值仿真证明了该控制器的有效性.Abstract: Flapping wing micro aerial vehicle (FWMAV) plays an important role in the research and application of aircraft, due to its significant advantages, such as high flight efficiency, low weight, low energy conservation, high flexibility and so on. Currently, the attitude trajectory tracking control of FWMAV has become a research hotspot in the field of aircraft control. To this end, an anti-disturbance controller based on parallel intelligence theory is proposed in this paper. Specifically, via the construction of artificial systems (A), computational experiments (C), and parallel execution (P), the proposed controller can effectively address the disturbance issue in FWMAV attitude tracking. Moreover, the effectiveness and feasibility of the proposed controller are proved by theoretical analyses and numerical simulations.
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表 1 控制器性能比较
Table 1 Comparison of performance among different controllers
$e_\theta $ (rad) $e_\phi$ (rad) $e_ \psi$(rad) 平均值 标准差 平均值 标准差 平均值 标准差 参考文献[14]中的控制器 (81) −0.0288 0.2483 −0.0166 0.3890 −0.0241 0.6696 ND 抗扰动控制器 (恒定扰动) −0.0162 0.0040 −0.0192 0.0185 −0.0101 0.0019 ND 抗扰动控制器 (线性时变扰动) −0.0038 0.0040 −0.0065 0.0200 −0.0029 0.0029 ND 抗扰动控制器 (有界随机扰动) −0.0021 0.0032 −0.0048 0.0199 −0.0020 0.0028 ND 抗扰动控制器 (正弦扰动) −0.0004 0.0043 −0.0033 0.0202 −0.0010 0.0038 -
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