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Robust Flare Phase Auto Landing of Aircrafts, Based on Modified ASBO

机译:强大的耀斑阶段汽车着陆飞机,基于改进的ASBO

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摘要

The presented research work is focused on automatic flight landing control of an aircraft for synthesis of optimal flare phase with considering the dynamic deflection angle as a control parameter. The behavior of the aircraft has considered in terms of four first-order differential equations and an explicit one step Runge Kutta has an order of 4 to 5 has applied to solve that. Computational intelligence based approach; modified adaptive social behavior optimization (mASBO) has applied to estimate the optimum deflection angles on discrete time to deliver the desired flare phase performances. The proposed modification in adaptive social behavior optimization has a better balance between exploration and exploitation by providing a competitive environment for leader selection, in result, faster convergence achieved. Height based on ascent rate controlling function presented here provides an adaptive control mechanism to obtain the desired landing performances in the presence of change in starting landing altitude in compare of predefined reference altitude due to poor visibility or wind disturbance.
机译:提出的研究工作专注于飞机的自动航班着陆控制,以便考虑动态偏转角作为控制参数来合成最佳闪光阶段。根据四个一阶微分方程,飞机的行为已经考虑,并且一个明确的一步跳kutta具有4到5的顺序来应用来解决。基于计算的智能方法;修改的自适应社会行为优化(Masbo)应用于估计离散时间的最佳偏转角,以提供所需的闪光相位性能。在适应性社会行为优化中提出的修改通过为领导者选择提供竞争环境,实现了更好的探索和剥削之间的平衡,从而实现了更快的融合。基于此处呈现的上升速率控制功能的高度提供了一种自适应控制机制,以获得由于可见性差或风扰动而在预定参考海拔高度的比较中起动的发生变化的所需着陆性能。

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