This paper designs a robust close-formation control system with dynamic estimation and compensation to advance unmanned aerial vehicle (UAV) close-formation flights to an engineer-implementation level. To characterize the wake vortex effect and analyze the sweet spot, a continuous horseshoe vortex method with high estimation accuracy is employed to model the wake vortex. The close-formation control system will be implemented in the trailing UAV to steer it to the sweet spot and hold its position. Considering the dynamic characteristics of the trailing UAV, the designed control system is divided into three control subsystems for the longitudinal, altitude, and lateral channels. Using linear active-disturbance rejection control (LADRC), the control subsystem of each channel is composed of two cascaded first-order LADRC controllers. One is responsible for the outer-loop position control and the other is used to stabilize the inner-loop attitude. This control system scheme can significantly reduce the coupling effects between channels and effectively suppress the transmission of disturbances caused by the wake vortex effect. Due to the cascade structure of the control subsystem, the correlation among the control parameters is very high. Therefore, sine-powered pigeon-inspired optimization is proposed to optimize the control parameters for the control subsystem of each channel. The simulation results for two UAV close formations show that the designed control system can achieve stable and robust dynamic performance within the expected error range to maximize the aerodynamic benefits for a trailing UAV.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Robust Control for UAV Close Formation Using LADRC via Sine-Powered Pigeon-Inspired Optimization


    Beteiligte:
    Guangsong Yuan (Autor:in) / Haibin Duan (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Re-entry Trajectory Design using Pigeon Inspired Optimization

    Sushnigdha, Gangireddy / Joshi, Ashok | AIAA | 2017


    UAV Formation Control Based on Multi-strategy Search Improved Pigeon-Inspired Optimization

    Sheng, Lei / Li, Hao / Niu, Quanmin et al. | Springer Verlag | 2024



    Protein secondary structure prediction via Pigeon-Inspired Optimization

    Wei Zheng, / Hemeng Sun, / Duan, Haibin | IEEE | 2016