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Adaptive True Proportional Navigation Guidance Based On Heuristic Optimization Algorithms

机译:基于启发式优化算法的自适应真正比例导航指导

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The PN-guidance (Proportional Guidance) still continues to be improved, because it is the simplest, cheapest and most reliable algorithm. One of the most important techniques to improve PN-guidance is to adapt the navigation constant depending on time. In this study, first, the entire adaptation methods for PN-guidance are classified, then the adaptation process is online achieved by using heuristic optimisation during guiding the missile. The novelty of this study is that the heuristic optimisation approach is used at the first time to update the navigation constant of PN-guidance. It is considered that having short program code, fast convergence speed and just simple algebraic computations without derivative are vital advantages of heuristic algorithms using into missile systems. In this scope, an Adaptive True-PN (ATPN) guidance algorithm is designed by optimising navigation constants varying according to the target behaviour. The results show that while the acceleration gap of the pitch axis decreases 21.8%, the acceleration gap of yaw axis reduces 39.68%. These reductions mean that while the missile guided by ATPN is maneuvering, it is exposed to less acceleration and less strain.
机译:PN-Guidance(比例指南)仍然继续提高,因为它是最简单,最便宜,最可靠的算法。提高PN-Guidance最重要的技术之一是根据时间调整导航常数。在本研究中,首先,对PN-Guidance的整个适应方法进行分类,然后通过在引导导弹期间使用启发式优化来实现适应过程。本研究的新颖性是,首次使用启发式优化方法来更新PN引导的导航常数。考虑到具有短节目代码,快速收敛速度和没有衍生的简单代数计算是启发式算法使用到导弹系统的重要优势。在此范围中,通过根据目标行为优化导航常量来优化导航常数来设计自适应True-PN(ATPN)引导算法。结果表明,虽然间距轴的加速间隙降低21.8%,但横摆轴的加速间隙降低了39.68%。这些减少意味着,虽然ATPN引导的导弹正在操纵,但它暴露于较少的加速和较少的应变。

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