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。
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.
出处
《声学与振动》
2020年第1期1-8,共8页
Open Journal of Acoustics and Vibration
基金
国家自然科学基金青年项目(批准号:11502161)、天津市自然科学基金青年项目(合同号:13JCQNJC04300).