计算机测量与控制2024,Vol.32Issue(2) :142-148,155.DOI:10.16526/j.cnki.11-4762/tp.2024.02.021

基于贝叶斯改进神经网络的电力无人机鲁棒姿态控制方法

Robust Attitude Control Method of Electric UAV Based on Bayesian Improved Neural Network

严永锋 任涛 王涛 吴烜 吴琳 李文
计算机测量与控制2024,Vol.32Issue(2) :142-148,155.DOI:10.16526/j.cnki.11-4762/tp.2024.02.021

基于贝叶斯改进神经网络的电力无人机鲁棒姿态控制方法

Robust Attitude Control Method of Electric UAV Based on Bayesian Improved Neural Network

严永锋 1任涛 1王涛 1吴烜 1吴琳 1李文1
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作者信息

  • 1. 武汉电力职业技术学院电网建设工程系,武汉 430000;国网湖北省电力有限公司技术培训中心,武汉 430000
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摘要

针对电力无人机在工作状态下受到外部因素干扰导致无法精准控制运动姿态的问题,提出基于贝叶斯改进神经网络的电力无人机鲁棒姿态控制方法;综合考虑电力无人机的组成结构、运动以及动力原理,构建电力无人机数学模型,利用传感器设备检测电力无人机的实时位姿,采用飞行路线规划的方式确定姿态控制目标;在考虑风场威胁条件和故障状态的情况下,利用贝叶斯改进神经网络计算无人机的姿态控制量,以鲁棒姿态控制器作为硬件支持,实现鲁棒姿态控制;通过性能测试得出结论:优化设计方法的姿态角控制误差始终低于0.2°,且在3种不同风场工况下,控制误差的波动程度不高于0.5°,与传统方法相比,优化设计方法在姿态控制精度和鲁棒性方面具有明显优势.

Abstract

Aiming at the problem that electric UAV cannot precisely control its motion attitude due to the interference of external factors,a robust attitude control method for the electric UAV based on Bayesian improved neural network is proposed.The mathe-matical model of electric UAV is established by considering the composition,motion and dynamic principle of the electric UAV.The sensor equipment is used to detect the real-time pose of the electric UAV,and the attitude control target is determined by the flight path planning way.Considering the wind threat condition and fault state,the attitude control quantity of the UAV is calculated by u-sing Bayesian improved neural network,and the robust attitude controller is used as the hardware support to realize the robust atti-tude control.Through the performance test,it is concluded that under three different wind conditions,the attitude angle control error of the optimized method is always below 0.2°,and the fluctuation degree of the control error not exceeding 0.5°.Compared with the traditional method,the optimized design method has obvious advantages in the accuracy and robustness of attitude control.

关键词

贝叶斯网络/改进神经网络/电力无人机/姿态控制/鲁棒控制

Key words

Bayesian network/improved neural network/electric UAV/attitude control/robust control

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出版年

2024
计算机测量与控制
中国计算机自动测量与控制技术协会

计算机测量与控制

CSTPCD
影响因子:0.546
ISSN:1671-4598
参考文献量16
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