Since the tightly coupled, highly nonlinear and notoriously uncertain nature of hypersonic flight vehicle(HFV) dynamics, any state which does not meet the constraint may lead the system states to diverge. In this paper, differential flatness approach is applied to linearize the longitudinal model of HFV. According to the established trajectory, all the time-varying states and control inputs can be obtained by differential flatness approach, which is advantageous to protect states from exceeding the constraint before flight simulation. A state feedback controller is proposed. An improved particle swarm optimization algorithm is proposed to obtain the optimal parameters, which can ensure both convergence property of the system and large enough search space of parameters. A case study is presented to illustrate the effectiveness of the proposed methodology.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Trajectory tracking control based on improved particle swarm optimization


    Beteiligte:
    Wang, Yuxiao (Autor:in) / Chao, Tao (Autor:in) / Wang, Songyan (Autor:in) / Yang, Ming (Autor:in)


    Erscheinungsdatum :

    2016-08-01


    Format / Umfang :

    139702 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multiconstrained Ascent Trajectory Optimization Using an Improved Particle Swarm Optimization Method

    Mu Lin / Zhao-Huanyu Zhang / Hongyu Zhou et al. | DOAJ | 2021

    Freier Zugriff


    Trajectory Tracking and Control of Unmanned Aerial Vehicle (UAV): A Particle Swarm Optimization-Based Approach

    Sharma, Shreyansh / Singh, Abhinav Kumar / Singh, Omkar et al. | Springer Verlag | 2023


    UAV Swarm Trajectory Planning Based on a Novel Particle Swarm Optimization

    Luo, Jing / Liu, Jie / Liang, QianChao | Springer Verlag | 2022


    3D Reference Trajectory Optimization Using Particle Swarm Optimization

    Murrieta-Mendoza, Alejandro / Ruiz, Hugo / Kessaci, Sonya et al. | AIAA | 2017