首页> 中文期刊> 《西北工业大学学报》 >复杂不确定环境下 UCAV 自主攻击轨迹优化设计

复杂不确定环境下 UCAV 自主攻击轨迹优化设计

         

摘要

Aim.For dealing with the key problem of UCAV autonomous combat under uncertain environment , a Receding Horizon Control-Pseudospectral Method (RHC-PM) is proposed.Sections 1 through 3 of the full paper explain our method.The core of section 1 is that it designs the total frame of UCAV autonomous combat process , which is Fig.1.The core of section 2 consists of: (1) the kinematics and kinetics equations of UCAVs (eqs.(1));(2) the threat cost function based on dynamic RCS (eqs.(11)); (3) the trajectory optimization model of UCAV autonomous combat under uncertain environment (eqs.(15) ~(18)).The core of section 3 proposes a solving framework for the trajectory optimization problem of UCAV autonomous combat under uncertain environment (Fig. 3) and a RHC-PM method.Fig.1 shows the schematic diagram of the UCAV autonomous combat process ; BEM in Fig.1 is the optimal attack trajectory around which our design develops .In the RHC-PM algorithm, two things are done: (1) the optimal rolling strategy is used for solving the problems of limited visual domain of the UCAV and for solving the difficulties to deal with sudden threats and dimensionality disasters caused by the increasing state space under a large scale uncertain environment ; (2) the predictive programming is used to deal with the problem of local optimization brought in by the rolling strategy and to deal with the problems of combat trajectory calculation difficul -ties in limited time leading to the trajectory without a solution .The simulation results, presented in Figs.4 through 12 and Table 1, and their analysis show preliminarily that the RHC -PM algorithm can quickly program an optimal trajectory under complex and uncertain environment , thus proving its effectiveness.%  针对不确定环境下无人作战飞机(UCAV)自主攻击关键问题,提出一种滚动伪谱法求解最优攻击轨迹的策略。首先设计出 UCAV 自主攻击过程总体框架,随后建立了 UCAV 三自由度质点模型,基于动态 RCS 构建统一威胁模型,采用威胁等效的方法快速处理突发威胁,以滚动优化策略解决大规模不确定环境下 UCAV 视野域范围有限、不易处理突发威胁以及因规划空间增大而产生的维数灾难等问题,以预测规划解决滚动方法带来的局部最优问题以及可能面临的有限时间内攻击轨迹解算困难而无解的问题。数字仿真结果表明,该算法能以较高的速度和精度在复杂不确定环境中快速规划出满足约束要求的最优对地攻击轨迹,且精度高、跟踪效果好,从而证明了该算法的有效性。

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