For the firing accuracy problem of the moving tank with different speed and different road level, the modelling and optimization method of the projectile disturbances of the moving tank under the general driving conditions were studied. A high-dimensional multi-objective optimization method for the projectile disturbances of the moving tank considering the different driving conditions was proposed based on the sequential approximate optimization method. Therein, a projectile disturbance multi-disciplinary simulation model of the moving tank considering multiple nonlinear factors was built and the sliced Latin hypercube design method was introduced to apply the experimental design. On the basis, the BP neural network surrogate model of the projectile disturbances at muzzle-exit of the moving tank under the general driving conditions was established. With the genetic algorithm and the potential optimal criterion, the sample points were updated to improve the accuracy of the surrogate model during the optimization. The optimization results show that the projectile disturbances at muzzle-exit of the moving tank under the general driving conditions were reduced effectively, and the comprehensive firing accuracy of the moving tank was improved. The research can provide a reference for realizing the reasonable match between firing accuracy and mobility of the tank.

针对不同速度，不同道路高度的运动坦克的射击精度问题，研究了在一般行驶条件下运动坦克弹丸扰动的建模与优化方法。基于顺序近似优化方法，提出了一种考虑不同行驶条件的运动坦克弹丸扰动的高维多目标优化方法。在此基础上，建立了考虑多个非线性因素的运动坦克弹丸扰动多学科仿真模型，并引入切片拉丁超立方体设计方法进行了实验设计。在此基础上，建立了在一般行驶条件下，移动坦克炮口出口弹丸扰动的BP神经网络模拟模型。利用遗传算法和潜在的最佳准则，对采样点进行了更新，以提高优化过程中替代模型的准确性。优化结果表明，在常规行驶条件下，有效降低了移动坦克炮口出射时的弹丸干扰，提高了移动坦克的综合射击精度。该研究可为实现射击精度与坦克机动性之间的合理匹配提供参考。提高了移动坦克的综合射击精度。该研究可为实现射击精度与坦克机动性之间的合理匹配提供参考。提高了移动坦克的综合射击精度。该研究可为实现射击精度与坦克机动性之间的合理匹配提供参考。