Longitudinal parameter identification of a small unmanned aerial vehicle based on modified particle swarm optimization

This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle (UAV) through modified particle swam optimization (PSO). The procedure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems (MEMS) inertial measuring element and a global positioning system (GPS) receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration (SRPSO). Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.