Fractional-order controllers optimized via heterogeneous comprehensive learning pigeon-inspired optimization for autonomous aerial refueling hose–drogue system

Abstract

Dynamic modeling and control system design for the hose–drogue system (HDS) in the docking stage of autonomous aerial refueling (AAR) are investigated in this paper. The dynamics and kinematics of hose are modeled via a finite-segment multi-body method, which describes the hose–drogue assembly as a link-connected system. A controllable drogue is connected to the hose for automatically stabilizing the drogue's relative position under the influences of tanker trailing vortex, receiver bow wave, atmospheric turbulence, gust, and wind shear. Thus, a drogue position control law based on fractional-order method is designed to resist the multi-wind disturbances. Noting that it is difficult to tune the parameters of fractional-order controller (FOC), a modified pigeon-inspired optimization (PIO), the hybrid of heterogeneous comprehensive learning strategy and PIO (HCLPIO), is carried out to optimize the parameters of FOC. The simulation results show that the proposed optimized fractional-order feedback controllers effectively stabilize the controllable drogue to swing within an acceptable range.