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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
收稿日期:2011-12-14,
修回日期:2012-01-18,
网络出版日期:2012-06-10,
纸质出版日期:2012-06-10
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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.
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。
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.
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