Abstract:

To improve the generality and computational efficiency of robust trajectory optimization technology under multi parameter uncertainty, a robust trajectory optimization method based on stochastic response surface method and polynomial chaos is designed. Firstly, non-intrusive polynomial chaos is combined with stochastic response surface, and a Latin hypercube sampling strategy is introduced to establish a multi-dimensional uncertainty quantification model, which realizes the effective and accurate transformation of the uncertain optimization problem. Secondly, combining the model with the convex optimization method, a trajectory optimization solution strategy based on the sequential convex optimization algorithm is designed to realize the rapid solution of the high-dimensional deterministic optimization problem. Finally, a hypersonic glide trajectory optimization problem considering multi parameter uncertainty such as initial state and process parameters is simulated and compared with the existing methods. The results show that compared with the traditional deterministic trajectory optimization algorithm, the proposed method can obtain the hypersonic glide trajectory with both reliability and robustness. Compared with the existing robust trajectory optimization methods, the proposed method has considerable accuracy and significant computational efficiency, which can ensure the efficiency and reliability of the robust trajectory optimization trajectory generation when the dimension of random variables increases.

Key words: uncertainty, robust trajectory optimization, polynomial chaos, stochastic response surface, convex optimization, hypersonic glide