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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Predator-Prey Pigeon-Inspired Optimization for UAV ALS Longitudinal Parameters Tuning
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Predator-Prey Pigeon-Inspired Optimization for UAV ALS Longitudinal Parameters Tuning

机译：捕食者-猎物鸽启发的无人机ALS纵向参数优化优化

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摘要

This paper presents a predator-prey pigeon-inspired optimization (PPPIO) algorithm for an automatic landing system of a fixed-wing unmanned aerial vehicle (UAV) in the longitudinal plane. Apitch command autopilot and two types of approach power compensators are presented and evaluated in automatic landing. The design of a glide slope command system and an approach power compensator are converted to a finite-dimensional optimization problem. The longitudinal flight controller parameters are optimized by the proposed PPPIO algorithm. The differences between the two proposed approach power compensators are also analyzed. The proposed optimization process can guarantee the control gains vector converge to an approximate optimal solution, and it is computationally much more efficient. Simulation results are presented to demonstrate that this approach helps solve control system optimization problems for different criteria and attains a rather accurate result. As verified by these simulation results, the proposed automatic landing system can help improve UAV's performance during the landing phase.
机译：本文提出了一种固定翼无人飞行器（UAV）在纵向平面上自动着陆系统的捕食者-猎物鸽启发式优化（PPPIO）算法。在自动着陆中介绍并评估了Apitch命令自动驾驶仪和两种进近功率补偿器。将滑行斜率指令系统和进近功率补偿器的设计转换为有限维优化问题。纵向飞行控制器参数通过提出的PPPIO算法进行了优化。还分析了两种拟议的方法功率补偿器之间的差异。所提出的优化过程可以保证控制增益向量收敛到近似最优解，并且计算效率更高。仿真结果表明，该方法有助于解决针对不同标准的控制系统优化问题，并获得相当准确的结果。这些仿真结果验证了所提出的自动着陆系统可以在着陆阶段帮助提高无人机的性能。

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