研究无人作战飞机(UCAV)在对地攻击阶段的武器投放轨迹规划问题。针对传统方法在处理复杂的飞行器运动学、动力学约束上存在的困难,提出了一种基于Gauss伪谱法(GPM)的求解策略。首先,为了最大程度地逼近实际飞行环境,对UCAV的气动力特性、发动机推力特性、油耗特性及大气环境特性进行了高精度拟合,并充分考虑了飞行器各种飞行性能约束和战场环境约束;其次,采用快速求解算法计算制导炸弹的可投放区(LAR)包络,将其作为终端约束来确保攻击的命中概率;然后利用GPM将轨迹规划问题转化为非线性规划问题,在此基础上采用序列二次规划(SQP)算法求得最优解。为了提升计算效率及降低初值设置的难度,设计了多步迭代优化策略。对时间最优和燃料最优轨迹优化问题进行了仿真验证,结果表明该方法能够以较高的精度和速度生成真实可行的最佳武器投放轨迹。
This paper studies the issue of generating optimal air-to-ground guided bomb delivery trajectories for unmanned combat aerial vehicles (UCAVs), and proposes a strategy based on the Gauss pseudospectral method (GPM) to deal with difficulties of traditional methods in processing vehicle kinematic and dynamic constraints. First, a high-fidelity 3-DOF nonlinear model of a UCAV is built which takes into consideration its aerodynamic characteristics, thrust and fuel consumption characteristics and atmospheric characteristics. Second, a fast algorithm is developed for searching the envelope of a guided bomb’s launch acceptable region (LAR), which is expressed as a final constraint in order to ensure attack accuracy. Third, GPM transforms the trajectory planning problem into a nonlinear programming problem, which can be solved using a sequential quadratic programming (SQP) algorithm. To improve computation efficiency and reduce the complexity of initial guess, a multistage iterative optimization strategy is presented. Finally, numerical examples for a minimum time-consumption trajectory as well as a minimum fuel-consumption trajectory are used to demonstrate the merits of the proposed algorithm. The results show that the algorithm can generate both feasible and optimal weapon delivery trajectories.
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