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Volume 8 Issue 1
Jan.  2021

IEEE/CAA Journal of Automatica Sinica

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Wei He, Xinxing Mu, Liang Zhang and Yao Zou, "Modeling and Trajectory Tracking Control for Flapping-Wing Micro Aerial Vehicles," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 148-156, Jan. 2021. doi: 10.1109/JAS.2020.1003417
Citation: Wei He, Xinxing Mu, Liang Zhang and Yao Zou, "Modeling and Trajectory Tracking Control for Flapping-Wing Micro Aerial Vehicles," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 148-156, Jan. 2021. doi: 10.1109/JAS.2020.1003417

Modeling and Trajectory Tracking Control for Flapping-Wing Micro Aerial Vehicles

doi: 10.1109/JAS.2020.1003417
Funds:  This work was supported in part by the National Natural Science Foundation of China (61933001, 62061160371), Joint Funds of Equipment Pre-Research and Ministry of Education of China (6141A02033339), and Beijing Top Discipline for Artificial Intelligent Science and Engineering, University of Science and Technology Beijing
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  • This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles (FWMAVs) in the longitudinal plane. First of all, the kinematics and dynamics of the FWMAV are established, wherein the aerodynamic force and torque generated by flapping wings and the tail wing are explicitly formulated with respect to the flapping frequency of the wings and the degree of tail wing inclination. To achieve autonomous tracking, an adaptive control scheme is proposed under the hierarchical framework. Specifically, a bounded position controller with hyperbolic tangent functions is designed to produce the desired aerodynamic force, and a pitch command is extracted from the designed position controller. Next, an adaptive attitude controller is designed to track the extracted pitch command, where a radial basis function neural network is introduced to approximate the unknown aerodynamic perturbation torque. Finally, the flapping frequency of the wings and the degree of tail wing inclination are calculated from the designed position and attitude controllers, respectively. In terms of Lyapunov’s direct method, it is shown that the tracking errors are bounded and ultimately converge to a small neighborhood around the origin. Simulations are carried out to verify the effectiveness of the proposed control scheme.

     

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    Highlights

    • This paper formulates the aerodynamic force and torque generated by the actual flapping frequency of flapping wings and tail wing inclination when constructing the system model of the FWMAV. Moreover, a hierarchical framework is introduced to exploit the cascaded structure of the established model for control scheme development.
    • This paper considers the unknown aerodynamic perturbation of flapping wings on the torque generated by the tail wing. A radial basis function neural network is introduced to estimate and compensate for this perturbation and for improving tracking accuracy.
    • This paper designs a bounded position controller with hyperbolic tangent functions to guarantee a bounded aerodynamic force. Also, this design effectively alleviates the coupling between the closed-loop position and attitude error systems, and thus facilitates the stability analysis greatly.

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