The flapping-wing aerial vehicle (FWAV) has appealed to more and more researchers recently owing to its outstanding performance in various domains and the development of some related technologies. The research on autonomous flight control of the FWAV involves many challenges and is still in nascent stages. In this work, we develop an FWAV with a mass of 14.1 g and build a vision-based experimental platform. A model-based controller is proposed on the basis of theory and simulation results prove its effectiveness. A PID control algorithm based on visual measurement is utilized to achieve the height-keeping control of the FWAV, and a software platform is designed to record the flight status determined using Euler angles and position information.
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Duan H B, Li H, Luo Q N, et al. A binocular vision-based UAVs autonomous aerial refueling platform. Sci China Inf Sci, 2016, 59: 053201
Mackenzie D. A flapping of wings. Science, 2012, 335: 1430–1433
Julian R C, Rose C J, Hu H, et al. Cooperative control and modeling for narrow passage traversal with an ornithopter MAV and lightweight ground station. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Minnesota, 2013. 103–110
de Croon G C H E, Perçin M, Remes B D W, et al. The DelFly. Berlin: Springer Netherlands, 2016
Ramezani A, Chung S J, Hutchinson S. A biomimetic robotic platform to study flight specializations of bats. Sci Rob, 2017, 2: eaal2505
Phan H V, Truong Q T, Park H C. Implementation of initial passive stability in insect-mimicking flapping-wing micro air vehicle. Int J Intell Unman Syst, 2015, 3: 18–38
Ma K Y, Chirarattananon P, Fuller S B, et al. Controlled flight of a biologically inspired, insect-scale robot. Science, 2013, 340: 603–607
Jiang Y, Yang C, Dai S, et al. Deterministic learning enhanced neutral network control of unmanned helicopter. Int J Advanced Robot Syst, 2016, 13: 1–12
Xu B, Yang C, Pan Y. Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle. IEEE Trans Neural Netw Learn Syst, 2015, 26: 2563–2575
He W, Zhang S. Control design for nonlinear flexible wings of a robotic aircraft. IEEE Trans Control Syst Tech, 2017, 25: 351–357
He W, Lv T, Chen Y, et al. Modeling and vibration control of flexible wings with output constraint. In: Proceedings of the 12th IEEE World Congress on the Intelligent Control and Automation (WCICA), Guilin, 2016. 1141–1146
Tay W B, van Oudheusden B W, Bijl H. Numerical simulation of X-wing type biplane flapping wings in 3D using the immersed boundary method. Bioinspir Biomi, 2014, 9: 036001
Banazadeh A, Taymourtash N. Adaptive altitude and position control of an insect-like flapping wing air vehicle. Nonlinear Dyn, 2016, 85: 47–66
Krstic M, Kanellakopoulos I, Kokotovic P V. Nonlinear and Adaptive Control Design. New York: Wiley, 1995
Slotine J J E, Li W. Applied Nonlinear Control. Englewood Cliffs: Prentice-Hall, 1991
This work was supported by National Natural Science Foundation of China (Grant Nos. 61522302, 61520106009, 61533008), Beijing Natural Science Foundation (Grant No. 4172041), and Fundamental Research Funds for the China Central Universities of USTB (Grant No. FRF-TP-15-005C1).
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He, W., Huang, H., Chen, Y. et al. Development of an autonomous flapping-wing aerial vehicle. Sci. China Inf. Sci. 60, 063201 (2017). https://doi.org/10.1007/s11432-017-9077-1
- flapping-wing aerial vehicle
- autonomous robot
- control design
- vision-based control
- unmanned aerial vehicle