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Journal of Bionic Engineering ›› 2020, Vol. 17 ›› Issue (4): 708-717.doi: 10.1007/s42235-020-0063-y

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Extended State Observer based Attitude Control of a Bird-like Flapping-wing Flying Robot

Keqiang Bai1*, YunZhi Luo2, Zhihong Dan3,4, Song Zhang3,4, Meiling Wang5, Qiumeng Qian4, Jun Zhong6*#br#

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  1. 1. School of Information Engineering, Southwest University of Science and Technology, Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Mianyang 621010, China
    2. Automation Research Institute Co., Ltd. of China South Industries Group Corporation, Mianyang 621000, China
    3. Science and Technology on Altitude Simulation Laboratory, AECC Sichuan Gas Turbine Establishment, Mianyang 621703, China
    4. AECC Sichuan Gas Turbine Establishment, Mianyang 621703, China
    5. Chinese Academy of Sciences Hefei Institutes of Physical Science, Hefei 230022, China
    6. College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China
  • Received:2020-02-11 Revised:2020-04-15 Accepted:2020-04-24 Online:2020-07-10 Published:2020-09-04
  • Contact: baisir@mail.ustc.edu.cn, zhongjun@hhu.edu.cn E-mail:10.1007/s42235-020-0063-y
  • About author:Keqiang Bai1*, YunZhi Luo2, Zhihong Dan3,4, Song Zhang3,4, Meiling Wang5, Qiumeng Qian4, Jun Zhong6*

Abstract: 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.

Key words: bionic, attitude control, flapping-wing flying robot, sliding mode adaptive control, extended state observer