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

Wei He; Xinxing Mu; Liang Zhang; Yao Zou

doi:10.1109/JAS.2020.1003417

Volume 8 Issue 1

Jan. 2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2021 > 8(1): 148-156

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

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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

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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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Author Bio:
Wei He (S’09–M’12–SM’16) received the B.Eng. and the M.Eng. degrees from the College of Automation Science and Engineering, South China University of Technology (SCUT), China in 2006 and 2008, respectively, and the Ph.D. degree from Department of Electrical and Computer Engineering, the National University of Singapore (NUS), Singapore in 2011. He is currently working as a Full Professor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing, China. He has co-authored 3 books published in Springer and published over 100 international journal and conference papers. He was awarded a Newton Advanced Fellowship from the Royal Society, UK. He was a recipient of the IEEE SMC Society Andrew P. Sage Best Transactions Paper Award. He is serving the Chair of IEEE SMC Society Beijing Capital Region Chapter. From 2018, he has been the Chair of Technical Committee on Autonomous Bionic Robotic Aircraft (TC-ABRA), IEEE Systems, Man and Cybernetics Society. He is serving as an Associate Editor of IEEE Transactions on Robotics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man, and Cybernetics: Systems, SCIENCE CHINA Information Sciences, IEEE/CAA Journal of Automatica Sinica, Assembly Automation, and an Editor of Journal of Intelligent Robotic Systems. His current research interests include robotics, distributed parameter systems, and intelligent control systems

Xinxing Mu received the B.Eng. and M.Eng. degrees from the School of Electrical Engineering, University of Jinan in 2015 and 2017, respectively. He is currently working toward the Ph.D. degree in control science and engineering with the School of Automation and Electrical Engineering, University of Science and Technology Beijing. His current research interests include FWMAV, intelligent control, and system modeling

Liang Zhang received the B.Eng. degree in intelligence science and technology from the School of Automation and Electrical Engineering, University of Science and Technology Beijing in 2019. He is currently working toward the Ph.D. degree with the School of Automation and Electrical Engineering, University of Science and Technology Beijing. His research interests include neural network control, vibration control, machine learning, and flexible structures

Yao Zou received the B.S. degree in automation from Dalian University of Technology (DUT) in 2010, and the Ph.D. degree in control science and engineering from Beijing University of Aeronautics and Astronautics in 2016. He was a Post-Doctoral Research Fellow with the Department of Precision Instrument, Tsinghua University from 2017 to 2018. He is currently an Associate Professor with the School of Automation and Electrical Engineering, University of Science and Technology Beijing. His current research interests include nonlinear control, unmanned aerial vehicle control, and multiagent control
Corresponding author: The authors are with the Institute of Artificial Intelligence, University of Science and Technology Beijing, and also with the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China (e-mail: weihe@ieee.org; muxinxing@126.com; 18811329798@163.com; zouyao@ustb.edu.cn)
Received Date: 2020-02-28
Revised Date: 2020-04-28
Accepted Date: 2020-06-03

Available Online: 2020-09-08

Abstract

Abstract

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.
- Flapping-wing micro aerial vehicles (FWMAVs),
- modeling,
- neural networks,
- trajectory tracking

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References(44)

References

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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.

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

doi: 10.1109/JAS.2020.1003417

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