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Control variable parameterisation with penalty approach for hypersonic vehicle reentry optimisation

机译:控制变量参数,具有惩罚途径劣质车辆再入优化

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摘要

An efficient trajectory optimisation approach combining the classical control variable parameterisation (CVP) with a novel smooth technology and two penalty strategies is developed to solve the trajectory optimal control problems. Since it is difficult to deal with path constraints in CVP method, the novel smooth technology is firstly employed to transform the complex constraints into one smooth constraint. Then, two penalty strategies are proposed to tackle the converted path and terminal constraints to decrease the computational complexity and improve the constraints satisfaction. Finally, a nonlinear programming problem, which approximates the original trajectory optimisation problem, is obtained. Error analysis shows that the proposed method has good convergence property. A general hypersonic cruise vehicle trajectory optimisation example is employed to test the performance of the proposed method. Numerical results show that the path and terminal conditions are well satisfied and better trajectory profiles are obtained, showing the effectiveness of the proposed method.
机译:开发了一种高效的轨迹优化方法,将经典控制变量参数化(CVP)与新颖的平滑技术和两种惩罚策略组合起来解决了轨迹最佳控制问题。由于难以处理CVP方法中的路径约束,因此首先采用新颖的平滑技术来将复杂约束转换为一个平滑约束。然后,提出了两种惩罚策略来解决转换的路径和终端约束,以降低计算复杂性并提高约束满足感。最后,获得了近似于原始轨迹优化问题的非线性编程问题。误差分析表明,该方法具有良好的收敛性。通用超声波巡航车辆轨迹优化实施例用于测试所提出的方法的性能。数值结果表明,路径和终端条件是很好的满足,获得了更好的轨迹轮廓,显示了所提出的方法的有效性。

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