Trajectory optimization problem for hypersonic vehicles has long been recognized as a difficult problem. This paper brings control constraints into the trajectory optimization to make the optimal trajectory meet the requirements of control performance. The strong nonlinear characteristic of the ascent phase aerodynamics makes the trajectory optimization problem difficult to be solved by the optimal control theory. A trajectory optimization algorithm based on the improved pigeon-inspired optimization (PIO) algorithm is proposed to solve the complex trajectory optimization problem under multiple constraints. To overcome the obstacle of premature convergence and deceptiveness, the evolutionary strategy of qubit in quantum evolutionary algorithm (QEA) is introduced into the PIO to maintain population diversity and judge the optimal solution. To handle constraints, the penalty function is used to construct the fitness function. The optimal ascent trajectory is obtained by utilizing the improved PIO algorithm. Then, the trajectory inverse algorithm is used to verify the feasibility of the optimal trajectory to ensure that a feasible optimal trajectory is obtained. The comparison results show that the proposed algorithm outperforms particle swarm optimization (PSO) and standard PIO on trajectory optimization. Meanwhile, the simulation result shows that the performance of the optimal ascent trajectory with control constraints is improved and the trajectory is feasible. Therefore, the method is potentially feasible for solving the ascent trajectory optimization problem under control constraint for hypersonic vehicles.


    Access

    Download


    Export, share and cite



    Title :

    Minimum-Fuel Ascent of Hypersonic Vehicle considering Control Constraint Using the Improved Pigeon-Inspired Optimization Algorithm


    Contributors:
    Jiahao He (author) / Yanbin Liu (author) / Shuanglin Li (author) / Yue Tang (author)


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Minimum-Fuel Ascent of a Hypersonic Vehicle Using Surrogate Optimization

    Dalle, Derek J. / Torrez, Sean M. / Driscoll, James F. et al. | AIAA | 2014



    Tracking Control of Hypersonic Vehicle Considering Input Constraint

    Sun, Jing-guang / Song, Shen-min / Wu, Guan-qun | ASCE | 2017


    ASCENT TRAJECTORY OPTIMIZATION OF HYPERSONIC VEHICLE USING SWARM INTELLIGENT METHOD

    Wang, Z.-Y. / Chen, P. / Wang, Y.-L. et al. | British Library Conference Proceedings | 2021