Reentry Trajectory Optimization for a Hypersonic Vehicle Based on an Improved Adaptive Fireworks Algorithm
Reentry Trajectory Optimization for a Hypersonic Vehicle Based on an Improved Adaptive Fireworks Algorithm
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基于改进自适应烟花算法的高超声速飞行器再入轨迹优化
DOI：
10.1155/2018/8793908
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发表时间：
2018-04
影响因子：
1.4
通讯作者：
Yang Ye
中科院分区：
文献类型：
--
作者：
Wei Xing;Liu Lei;Wang Yongji;Yang Ye
同时满足边界条件和路径约束的高超声速飞行器再入最优轨迹的生成是一项具有挑战性的任务。作为一种较新的群体智能算法，自适应Fireworks算法(AFWA)在一些优化问题上表现出了良好的性能。然而，对于约束条件下的最优再入轨迹生成，由于包括烟花和火花在内的个体不能被整个群体很好地告知，AFWA有可能陷入局部最优。在本文中，我们提出了一种改进的AFWA来生成约束条件下的最优再入轨迹。首先，通过切比雪夫多项式插值将无限维的弹道优化问题转化为有限维的非线性规划问题，并通过路径约束得到攻角范围，降低了优化的难度。为了解决这一问题，提出了一种新的变异策略改进的AFWA，使烟花能够通过新的变异算子向更多的个体学习。该策略显着增强了烟花和火花之间的相互作用，从而增加了种群的多样性，提高了全局搜索能力。此外，还提出了一种基于自适应惩罚函数和距离度量的约束处理技术来处理多个约束。通过对高压飞行器两种再入方案的数值仿真，与其他优化方法进行比较，验证了改进的AFWA优化方法的有效性和有效性。
Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods.
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影响因子：
2.6
作者：
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通讯作者：
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影响因子：
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