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Modified shuffled frog leaping algorithm optimized control for air-breathing hypersonic flight vehicle

机译:用于空气呼吸超声波飞行车辆的改装减频青蛙跳跃算法优化控制

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摘要

This article addresses the flight control problem of air-breathing hypersonic vehicles and proposes a novel intelligent algorithm optimized control method. To achieve the climbing, cruising and descending flight control of the air-breathing hypersonic vehicle, an engineering-oriented flight control system based on a Proportional Integral Derivative (PID) method is designed for the hypersonic vehicle, which including the height loop, the pitch angle loop and the velocity loop. Moreover, as a variant of nature-inspired algorithm, modified shuffled frog leaping algorithm is presented to optimize the flight control parameters and is characterized by better exploration and exploitation than the standard shuffled frog leaping algorithm. A nonlinear model of air-breathing hypersonic vehicle is used to verify the dynamic characteristics achieved by the intelligent flight control system. Simulation results demonstrate that the proposed swarm intelligence optimized PID controllers are effective in achieving better flight trajectory and velocity control performance than the traditional controllers.
机译:本文解决了空气呼吸超声波车辆的飞行控制问题,提出了一种新颖的智能算法优化控制方法。为实现攀岩,巡航和下降飞行控制空气呼吸超声波的车辆,基于比例整体衍生物(PID)方法的基于工程导向的飞行控制系统,专为高超声速车辆而设计,包括高度环,间距角度环和速度环。此外,作为自然启发算法的变种,提出了改进的洗机青蛙跨越算法以优化飞行控制参数,其特点是比标准混合青蛙跳跃算法更好的探索和开发。空气呼吸超声波车辆的非线性模型用于验证智能飞行控制系统实现的动态特性。仿真结果表明,拟议的群体智能优化的PID控制器对于实现比传统控制器更好的飞行轨迹和速度控制性能有效。

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