Abstract
In this paper, the design and optimization method of rocket parameters based on the surrogate model and the trajectory simulation system of the 3-DOF air-launched rockets were established. The Gaussian kernel width determination method based on the relationship between local density and width is used to ensure the efficiency and reliability of the optimization method, and at the same time greatly reduces the amount of calculation. An adaptive sampling point updating method was established, which includes three stages: location sampling, exploration sampling, and potential optimal sampling of the potential feasible region. The adaptive sampling is realized by the distance constraint. Based on the precision of the surrogate model, the convergence end criterion was established, which can achieve efficient and reliable probabilistic global optimization. The objective function of the optimization problem was deduced to determine the maximum load mass and reasonable constraints were set to ensure that the rocket could successfully enter orbit. For solid engine rockets with the same take-off mass as Launcherone, the launch altitude and target orbit were optimized and analyzed, and verified by 3-DOF trajectory simulation. The surrogate-based optimization algorithm solved the problem of the overall parameter design optimization of the air-launched rocket and it provides support for the design of air-launched solid rockets.
Highlights
Air-launched rocket refers to relying on large aircraft as an air-launch platform, which carries the rocket to high altitude to release and launch, after a certain attitude adjustment, the rocket engine ignites and transports the load to the preset space orbit [1]
The trajectory of the air-launched rocket was optimized by using the surrogate-based optimization method
The precision of the surrogate model is significantly improved by the adaptive sampling point updating strategy and the kernel width estimation of the radial basis function, which balances the sampling exploration and development ability of the optimization method
Summary
Air-launched rocket refers to relying on large aircraft (large transport aircraft, cargo aircraft, strategic bombers, aircraft, etc.) as an air-launch platform, which carries the rocket to high altitude to release and launch, after a certain attitude adjustment, the rocket engine ignites and transports the load to the preset space orbit [1]. To solve the above problems, Zhou et al [19] proposed a multi-attribute comprehensive optimization design method based on variable weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) evaluation and particle swarm optimization algorithm fusion and took Euclidean distance as the optimization evaluation index to optimize the overall parameters of the missile. Where, d(x) is the minimum Euclidean distance between the new sample point and the original sample point, and N is the number of existing sample points This method can modify the surrogate-based optimization method to a strong ability of exploration, but it is difficult to converge globally. Nis the number of sample points, and xi, xj are the coordinates of sampling points
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