基于兹-QPSO的战斗机机动规避优化方法

摘要

Optimal evasion from guided missiles is crucial for the survival in air combat. Firstly,the fighter and missile are modeled as point-masses. The missile utilizes proportional navigation. Then,the optimal control problem is transformed into a nonlinear programming problem with the direct multiple shooting method. By using phase angle-encoded and quantum-behaved particle swarm optimization(Ɵ-QPSO) algorithm based on rolling optimization concept,optimal results of the NLP problem can be quickly obtained,and the control factors can be updated via Model Predictive Control. Finally,simulation shows that the feasibility of the method and the effectiveness of the algorithm.%规避导弹攻击对于提高战斗机生存能力具有重要意义。首先，建立战斗机和导弹的运动模型及导弹导引律模型，采用直接多重打靶的参数化方法，将机动规避最优控制问题转化为非线性规划问题；采用相位角编码量子粒子群优化算法（兹-QPSO）实现参数寻优，并结合滚动优化的思想，利用模型预测控制得到规避轨迹闭环解和战斗机的实时控制量。最后仿真验证了该方法的合理性和算法的有效性。