基于BP神经网络的小型四旋翼无人机的PID控制
PID Control of Quadrotor UAV Based on BP Neural Network
DOI: 10.12677/OJAV.2020.81001, PDF,    国家自然科学基金支持
作者: 曹俊灵：天津市联大通讯发展有限公司，天津；钟 顺*, 孙子涵：天津大学力学系，天津；韩佳杰, 王 超：河北瑞兆激光再制造股份有限公司，河北 唐山
关键词: PID控制；四旋翼无人机；BP神经网络；机器学习；PID； Quadrotor； BP Neural Network； Machine Learning
摘要: 四旋翼无人机是一个强耦合、欠驱动的多自由度非线性系统，因此对四旋翼无人机的控制十分的重要。本文基于BP神经网络训练的方式对PID控制器中的参数进行优化。结果表明，和传统PID控制相比，BP神经网络得到的结果有更佳的控制效果，为小型四旋翼无人机的控制提供了新的方法和思路。
Abstract: The quadrotor UAV is a strong coupling and underactuated multi-degree of freedom nonlinear sys-tem, so the control of the quadrotor UAV is very important. This work optimizes the parameters of PID controller based on BP neural network. The results indicate that compared with the traditional PID control, the results from BP neural network have better performance, which would provide a new method and idea for the control design of small quadrotor UAV.
文章引用：曹俊灵, 钟顺, 孙子涵, 韩佳杰, 王超. 基于BP神经网络的小型四旋翼无人机的PID控制[J]. 声学与振动, 2020, 8(1): 1-8. https://doi.org/10.12677/OJAV.2020.81001

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