Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 47, Issue 10, Pages 3452-3465Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2017.2720801
Keywords
Adaptive control; disturbance observer design; flapping wing micro aerial vehicle (FWMAV); neural networks (NNs); robotics
Categories
Funding
- National Natural Science Foundation of China [61522302, 61761130080, 61520106009, 61533008]
- Royal Society, U.K. [NA160436]
- Beijing Natural Science Foundation [4172041]
- Fundamental Research Funds for the China Central Universities of USTB [FRF-BD-16-005A, FRF-TP-15-005C1]
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The research of this paper works out the attitude and position control of the flapping wing micro aerial vehicle (FWMAV). Neural network control with full state and output feedback are designed to deal with uncertainties in this complex nonlinear FWMAV dynamic system and enhance the system robustness. Meanwhile, we design disturbance observers which are exerted into the FWMAV system via feedforward loops to counteract the bad influence of disturbances. Then, a Lyapunov function is proposed to prove the closed-loop system stability and the semi-global uniform ultimate boundedness of all state variables. Finally, a series of simulation results indicate that proposed controllers can track desired trajectories well via selecting appropriate control gains. And the designed controllers possess potential applications in FWMAVs.
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