Modeling and Adaptive Control for Flapping-Wing Micro Aerial Vehicle
Flight quality of flapping-wing micro aerial vehicle (FMAV) depends much upon efficient control of flight attitude. So, an accurate model of flight attitude is of utmost importance. The fly mechanism of birds and big insects, especially the motion rule of wings were investigated to establish a complete dynamic model and mathematical model for flight attitude of FMAV. The design of attitude controller is challenging due to the complexity of the flight process, and the difficulty is system uncertainty, nonlinearity, multi-coupled parameters, and all kinds of disturbances. To control the attitude movement effectively, a global adaptive H∞ control strategy was constructed that the controller synthesis was based on Lyapunov function instead of solving the Hamilton-Jacobi-Isaacs (HJI) partial differential equation. The method overcomes the impact of time-varying parameters and unknown disturbances to the system. Simulation results support the effectiveness of the dynamic model and the control strategy.
Keywordsflapping-wing micro aerial vehicle dynamic model nonlinearity adaptive H∞ control attitude control
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- 1.Wzorek, M., Conte, G., Rudol, P., Merz, T., Duranti, S., Doherty, P.: From Motion Planning to Control – A Navigation Framework for an Autonomous Unmanned Aerial Vehicle. In: Proc. of the 21st Bristol International UAV Systems Conference (2006)Google Scholar
- 2.Le, B.F., Mahony, R., Hamel, T., Binetti, P.: Adaptive Filtering and Image Based Visual Servo Control of a Ducted Fan Flying Robot. In: Proc. of the 45th IEEE Conference on Decision & Control, San Diego, CA, USA, December 13-15, pp. 1751–1757 (2006)Google Scholar
- 3.Scherer, S., Singh, S., Chamberlain, L.J., Saripalli, S.: Flying Fast and Low Among Obstacles. In: Proc. of the International Conference on Robotics & Automation, Roma, Italy, April 10-14, pp. 2023–2029 (2007)Google Scholar
- 4.La, C.M., Papageorgiou, G., William, C.M., Kanade, T.: Integrated Modeling and Robust Control for Full-envelope Flight of Robotic Helicopters. In: Proc. of the 2003 IEEE International Conference on Robotics & Automation, Taipei, Taiwan, September 14-19, pp. 552–557 (2003)Google Scholar
- 5.Pounds, P., Mahony, R., Hynes, P., Roberts, J.: Design of a Four Rotor Aerial Robot. In: Australian Conference on Robotics & Automation, Auckland, November 27-29, pp. 145–150 (2002)Google Scholar
- 6.Lasek, M., Pietrucha, J., Zlocka, M., Sibilski, K.: Analogies Between Rotary and Flapping Wings From Control Theory Point of View. AIAA-2001–4002 (2001)Google Scholar
- 7.Sanjay, P.S., Michael, H.D.: The Aerodynamic Effects of Wing Rotation and A Revised Quasi-steady Model of Flapping Flight. Journal of Experimental Biology 205, 1087–1096 (2002)Google Scholar
- 8.Yan, J., Wood, R.J., Avadhanula, S., Sitti, M., Fearing, R.S.: Towards Flapping Wing Control for a Micromechanical Flying Insect. In: Proceedings of the 2001 IEEE International Conference on Robotics & Automation, Seoul, Korea, May 21-26, pp. 3901–3908 (2001)Google Scholar
- 9.Schenato, L., Campolo, D., Sastry, S.: Controllability Issues in Flapping Flight for Biomimetic Micro Aerial Vehicles (MAVs). In: Proceedings of the 42nd IEEE International Conference on Decision & Control, Maui, Hawaii, USA, pp. 6441–6447 (December 2003)Google Scholar
- 10.Deng, X.Y., Schenato, L., Sastry, S.S.: Model Identification and Attitude Control for a Micromechanical Flying Insect Including Thorax and Sensor Models. In: Proc. of IEEE International Conference on Robotics & Automation, Teipei, Taiwan, September 14-19, pp. 1152–1157 (2003)Google Scholar