Adaptive control of quadrotor MAV using interval type-II fuzzy neural network

CHEN Xiang-jian; LI Di; XU Zhi-jun; SU Dong-feng

doi:10.3788/OPE.20122006.1334

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Adaptive control of quadrotor MAV using interval type-II fuzzy neural network

更新时间：2020-08-12

- Adaptive control of quadrotor MAV using interval type-II fuzzy neural network
- Optics and Precision Engineering Vol. 20, Issue 6, Pages: 1334-1341(2012)
- 作者机构：
  
  1. 中国科学院长春光学精密机械及物理研究所,吉林长春,130033
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20122006.1334
  CLC： TP183;V249.12
- Received：14 December 2011，
  
  Revised：18 January 2012，
  
  Published Online：10 June 2012，
  
  Published：10 June 2012
- 稿件说明：
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陈向坚, 李迪, 续志军, 苏东风. 四旋翼微型飞行器的区间二型模糊神经网络自适应控制[J]. 光学精密工程, 2012,20(6): 1334-1341

CHEN Xiang-jian, LI Di, XU Zhi-jun, SU Dong-feng. Adaptive control of quadrotor MAV using interval type-II fuzzy neural network[J]. Editorial Office of Optics and Precision Engineering, 2012,20(6): 1334-1341
陈向坚, 李迪, 续志军, 苏东风. 四旋翼微型飞行器的区间二型模糊神经网络自适应控制[J]. 光学精密工程, 2012,20(6): 1334-1341 DOI： 10.3788/OPE.20122006.1334.

CHEN Xiang-jian, LI Di, XU Zhi-jun, SU Dong-feng. Adaptive control of quadrotor MAV using interval type-II fuzzy neural network[J]. Editorial Office of Optics and Precision Engineering, 2012,20(6): 1334-1341 DOI： 10.3788/OPE.20122006.1334.

摘要

针对四旋翼微型飞行器控制系统中存在不确定性、外界干扰等影响控制精度的问题

提出了基于区间二型模糊神经网络(IT_IIFNN)的四旋翼微型飞行器自适应控制方案。首先

根据四旋翼微型飞行器的动力学模型

设计了基于IT_IIFNN的四旋翼微型飞行器自适应控制器

该控制器由两部分构成

其中IT_IIFNN用来在线逼近系统不确定性;鲁棒补偿器用来实时补偿IT_IIFNN的逼近误差以及外界干扰。其次

利用Lyapunov稳定理论证明此飞行器控制系统闭环稳定性。最后

通过四旋翼微型飞行器样机来验证IT_IIFNN自适应控制器的优越性。验证结果显示

在加入风速为1.5 m/s的外界干扰条件下

跟踪误差可近似达到10

-2

。结果表明

IT_IIFNN自适应控制器具有良好的跟踪精度、稳定性及鲁棒性。

Abstract

The adaptive control scheme of a quadrotor Micro Aerial Vehicle (MAV) by using Interval Type-II Fuzzy Neural Network (IT_IIFNN) was proposed to improve the control accuracy that was declined by the uncertainty

external disturbances

etc

. Based on the quadrotor MAV dynamic modeling

an adaptive controller composing of two parts was designed by using the IT_IIFNN

in which the IT_IIFNN was developed to approximate the uncertainty function and a robust compensator was proposed to confront the approximate errors of IT_IIFNN and external disturbances in real-time. Moreover

the Lyapunor stability theory was taken to prove the stability of the closed-loop control system in the quadrotor MAV.Finally

the superiority of the adaptive controller was verified by a prototype of the quadrotor MAV

which is shown that the tracking error approximated is 10

-2

under the interference conditions of wind speed of 1.5 m/s.Experiments demonstrate that proposed control scheme can offer perfect tracking accuracy

stability and robustness.

关键词

Keywords

references

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