Attitude control system of quadrotor based on PID neural network

ZOU Yifei; LIU Wu; YAN Zhongwen; ZHANG Weiping; CUI Feng

doi:10.13873/J.1000-9787(2020)01-0068-03

Chinese

您当前的位置：

首页 >

文章列表页 >

Attitude control system of quadrotor based on PID neural network

更新时间：2025-09-11

- Attitude control system of quadrotor based on PID neural network
- Issue 1, Pages: 68-70+74(2020)
- 作者机构：
  
  微米/纳米加工技术国家级重点实验室上海市北斗导航与位置服务重点实验室上海交通大学电子信息与电气工程学院微纳电子学系
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)01-0068-03
  CLC： V249.1
- Published：2020
- 稿件说明：
移动端阅览
ZOU Yifei, LIU Wu, YAN Zhongwen, et al. Attitude control system of quadrotor based on PID neural network[J]. 2020, (1): 68-70+74.
DOI：

ZOU Yifei, LIU Wu, YAN Zhongwen, et al. Attitude control system of quadrotor based on PID neural network[J]. 2020, (1): 68-70+74. DOI： 10.13873/J.1000-9787(2020)01-0068-03.

摘要

针对PID控制对于四旋翼飞行器这类强耦合系统参数整定困难和控制稳定性不足的问题

提出了基于PID神经元网络(PIDNN)的新型控制算法

并设计了基于STM32微处理器的微飞行器。MATLAB系统仿真和飞行测试结果表明

相比于传统PID控制

PID神经元网络控制具有较快的稳定时间和较小的超调量

提高了系统的稳定性和自适应能力

同时实现了广义解耦。

Abstract

Aiming at the problem that the traditional PID controller has difficulty in parameter setting and lack of control stability for strongly coupled system such asquadrotor

a new type of control algorithm based on PID neural network（ PIDNN） is proposed. A micro quadrotor is designed based on STM32 microcontroller. The simulation of the system by MATLAB shows that compared with the traditional PID control

PID neural network control has faster stable time and less overshoot

which improves the stability and adaptive ability of the system

and generalized decoupling is realized at the same time.

关键词

Keywords

references

Views

394

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Four-rotor UAV track planning algorithm based on improved artificial potential field method

Quadrotor simulation and test system based on automatic reconstruction of virtual scene

INS attitude algorithm based on PID adaptive Kalman

Human fall detection system based on threshold analysis method

NO_x sensor special controller based on reference current control method

Related Author

JIANG Xiangju

DENG Ye

MEI Yanying

YANG Tao

DENG Shun

ZHANG Guoqiang

XIE Hao

LIU Chun

Related Institution

School of Automation and Electrical Engineering,Lanzhou Jiaotong University

Key Laboratory of Sichuan Province for Robot Technology Used for Special Environment

School of Information Engineering,Southwest University of Science and Technology

School of Computer Science and Information Engineering,Hefei University of Technology

School of Electrical and Automation Engineering, Hefei University of Technology

⁰