A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm

This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft. By using the flash memory integrated into the micro guide navigation control module, system records the data sequences of flight tests as inputs (control signals for servos) and outputs (aircraft's attitude and velocity information). After data preprocessing, the system constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive genetic algorithm. The identified model is verified by a series of simulations and tests. Comparison between flight data and the one-step prediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmanned aerial rotorcraft system. Based on the proposed dynamic model, the small unmanned aerial rotorcraft can perform hovering, turning, and straight flight tasks in real flight tests.