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A flight-dynamics oriented simulation model of a flapping-wing Micro Air Vehicle (MAV) has been developed. This concept is based on flapping flight performed in nature by insects or hummingbirds. An optimization of the flapping kinematics of the wing has been led, in order to maximize the mean lift and thus the payload. A neural network has been designed to reproduce the function shape of the wings movements, and the weights have been optimized using a genetic algorithm. Results show a lift gain from 30 to 40%, and corroborate also some mechanisms shown up through experiments.

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