The attitude control system of a flapping-wing flying robot plays an important role in the precise orientation and tracking of the robot. In this paper, the modeling of a bird-like micro flapping-wing system is introduced, and the design of a sliding mode controller based on an Extended State Observer (ESO) is described. The main design difficulties are the control law and the adaptive law for the attitude control system. To address this problem, a sliding mode adaptive extended state observer algorithm is proposed. Firstly, a new extended state approximation method is used to estimate the final output as a disturbance state. Then, a sliding mode observer with good robustness to the model approximation error and external disturbance is used to estimate the system state. Compared with traditional algorithms, this method is not only suitable for more general cases, but also effectively reduces the influence of the approximation error and interference. Next, the simulation and experiment example is given to illustrate the implementation process. The results show that the algorithm can effectively estimate the state of the attitude control system of the flapping-wing flying robot, and further guarantee the robustness of the model regarding error and external disturbance.

中文翻译：

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基于扩展状态观测器的鸟形扑翼飞行机器人的姿态控制

扑翼飞行机器人的姿态控制系统在精确定位和跟踪机器人方面起着重要作用。本文介绍了一种鸟状微扑翼系统的建模，并描述了基于扩展状态观测器（ESO）的滑模控制器的设计。主要的设计难点是姿态控制系统的控制律和自适应律。为了解决这个问题，提出了一种滑模自适应扩展状态观测器算法。首先，使用一种新的扩展状态近似方法来估计最终输出为干扰状态。然后，使用对模型逼近误差和外部干扰具有良好鲁棒性的滑模观测器来估计系统状态。与传统算法相比，该方法不仅适用于更一般的情况，而且有效地减小了近似误差和干扰的影响。接下来，给出了仿真和实验示例来说明实现过程。结果表明，该算法可以有效地估计扑翼飞行机器人姿态控制系统的状态，并进一步保证了模型在误差和外界干扰方面的鲁棒性。