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Optimal Ascent Guidance for Air-Breathing Launch Vehicle Based on Optimal Trajectory Correction

机译：基于最优轨迹修正的气载运载火箭最优升空制导

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摘要

An optimal guidance algorithm for air-breathing launch vehicle is proposed based on optimal trajectory correction. The optimal trajectory correction problem is a nonlinear optimal feedback control problem with state inequality constraints which results in a nonlinear and nondifferentiable two-point boundary value problem (TPBVP). It is difficult to solve TPBVP on-board. To reduce the on-board calculation cost, the proposed guidance algorithm corrects the reference trajectory in every guidance cycle to satisfy the optimality condition of the optimal feedback control problem. By linearizing the optimality condition, the linear TPBVP is obtained for the optimal trajectory correction. The solution of the linear TPBVP is obtained by solving linear equations through the Simpson rule. Considering the solution of the linear TPBVP as the searching direction for the correction values, the updating step size is generated by linear search. Smooth approximation is applied to the inequality constraints for the nondifferentiable Hamiltonian. The sufficient condition for the global convergence of the algorithm is given in this paper. Finally, simulation results show the effectiveness of the proposed algorithm.
机译：提出了一种基于最优轨迹校正的呼吸运载火箭最优制导算法。最优轨迹校正问题是具有状态不等式约束的非线性最优反馈控制问题，这会导致非线性且不可微的两点边值问题（TPBVP）。车载TPBVP很难解决。为了降低机载计算成本，本文提出的制导算法在每个制导周期内对参考轨迹进行修正，以满足最优反馈控制问题的最优条件。通过线性化最优条件，可以获得线性TPBVP用于最优轨迹校正。线性TPBVP的解是通过使用Simpson规则求解线性方程来获得的。将线性TPBVP的解作为校正值的搜索方向，通过线性搜索生成更新步长。光滑近似适用于不可微哈密顿量的不等式约束。给出了算法全局收敛的充分条件。最后，仿真结果表明了该算法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第16期|313197.1-313197.11|共11页
  • 作者

    Lu Xuefang; Wang Yongji; Liu Lei;

  • 作者单位

    Huazhong Univ Sci & Technol, Sch Automat, Key Lab Minist Educ Image Proc & Intelligent Cont, Wuhan 430074, Peoples R China.;

    Huazhong Univ Sci & Technol, Sch Automat, Key Lab Minist Educ Image Proc & Intelligent Cont, Wuhan 430074, Peoples R China.;

    Huazhong Univ Sci & Technol, Sch Automat, Key Lab Minist Educ Image Proc & Intelligent Cont, Wuhan 430074, Peoples R China.;

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