A system identification method for small unmanned aerial rotorcraft based on the adaptive genetic algorithm

A system identification method for the small unmanned aerial rotorcraft (SUAR) using adaptive genetic algorithm is proposed. Using the on-board sensor equipments, the system acquires the corresponding input information (control signals for digital servos) and output information (attitude and velocity information, etc. of the small unmanned aerial rotorcraft). After data pre-processing, a high precision dynamic model is constructed by using the adaptive genetic algorithm. And the effectiveness of the proposed dynamic model is verified by simulations and experiments. Experiments show that SUAR based on the proposed dynamic model can perform hovering and straight flight accurately.