An evaluation strategy of trajectory optimization algorithms for hypersonic reentry vehicle

A comprehensive evaluation strategy is proposed to deal with the evaluation of various trajectory optimization algorithms for the hypersonic reentry vehicle. An integrated index system is established by taking the stability and real-time performance of each algorithm itself as well as the feasibility, security, transitivity and optimality of its optimization result into account. And the calculation of index weights is transformed into an optimization problem based on the pairwise judgement matrix of the analytic hierarchy process, and the Euclidean distance and the number of violations are used as precision measures. The genetic algorithm is used to solve the optimization problem. Then, the normalized decision matrix is obtained, and a weighted grey technique for order preference by similarity to ideal solution (TOPSIS) is proposed by synthesizing the nearness degree in both the space and curve between the algorithm data and the ideal control groups to achieve the final evaluation results. Simulation results show that the proposed strategy uses objective data to quantify the performance of trajectory optimization algorithms, and forms a comparative evaluation standard for various algorithms. The strategy can help designers quickly select an optimal algorithm according to different mission requirements and avoid blindness and subjectivity. © 2016, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.