Active disturbance rejection control optimized via chaotic comprehensive learning pigeon-inspired optimization for flapping-wing aerial vehicle

Purpose This study aims to address the active disturbance rejection control (ADRC) problem of flapping-wing aerial vehicle (FWAV) under the influence of wind disturbances. Design/methodology/approach First, the six-degrees-of-freedom hummingbird model with model uncertainty is constructed to describe the FWAV. Considering the wind disturbances in the complex environment, the active disturbance rejection controllers are developed to improve the anti-disturbance ability and the control accuracy of FWAV. Then, a modified pigeon-inspired optimization (PIO), called chaotic comprehensive learning PIO (CCLPIO), is proposed to optimize the designed ADRC controllers of the FWAV’s rotational motion and translational motion, which intends to realize the optimal control effects and reduce the difficulties of parameter tuning. Findings The simulation results indicate that the proposed optimized ADRC controllers can effectively guarantee the FWAV to converge to the desired values. Originality/value This study develops an optimized active disturbance rejection control method to realize the steady flight of FWAV in the presence of wind disturbances.