Parameter optimization control of multi-rotor unmanned aerial vehicles based on adaptive differential evolution

Abstract Aiming at the problems of instability and underactuation encountered in the control process of traditional multi-rotor unmanned aerial vehicles, an adaptive differential evolution algorithm is designed to optimize the parameters of the sliding mode controller. The advantages of the fast convergence of the sliding mode controller and the global search of the evolutionary algorithm are combined for parameter optimization. The simulation results show that the sliding mode controller, after parameter optimization, has good stability.