基于PSO-SQP算法的空地导弹弹道优化

Trajectory Optimization of Air to Ground Missile Based on PSO-SQP Algorithm

利用高斯伪谱法(GPM)将空地导弹快速打击地面目标的弹道最优控制问题转化为非线性规划(NLP)问题;构建粒子群算法(PSO)对初始弹道进行求解,进而实现对序列二次规划(SQP)算法初值的优选;代入SQP算法中求解非线性规划问题。仿真结果表明,仅用随意选取初值的SQP算法求解弹道优化设计问题,很难求得最优解,利用PSO算法可以很好地解决SQP算法的初值依赖,增加得到最优解的可能性。上述算法流程可有效解决弹道最优控制问题,具有较强的全局寻优和局部精确搜索能力,在工程上易于实现,可为工程设计提供参考。

The optimal trajectory control problem was transformed into a Non-linear programming(NLP)problem by using the Gaussian pseudo-spectral method(GPM)for air-to-ground missiles rapidly hitting ground targets.The Particle swarm optimization(PSO)algorithm was constructed to solve the initial trajectory,and then the initial value of sequential quadratic programming(SQP)algorithm was optimized.It was substituted into SQP algorithm to solve the non-linear programming problem.The simulation results show that it is difficult to get the optimal solution only by using SQP algorithm with random initial value.PSO algorithm can solve the problem of initial value dependence of SQP algorithm and increase the possibility of getting the optimal solution.The above algorithm flow can effectively solve the trajectory optimal control problem,has strong global optimization and local accurate search ability,and is easy to implement in engineering,which can provide reference for engineering design.