[1]李洪梅,高 媛,陈向坚.基于二型模糊神经网络的不确定混沌系统鲁棒性自适应控制[J].南京理工大学学报(自然科学版),2019,43(04):432-438.[doi:10.14177/j.cnki.32-1397n.2019.43.04.008]
 Li Hongmei,Gao Yuan,Chen Xiangjian.Interval type II fuzzy neural network control based robust adaptivefor the synchronization of uncertain chaotic systems[J].Journal of Nanjing University of Science and Technology,2019,43(04):432-438.[doi:10.14177/j.cnki.32-1397n.2019.43.04.008]
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基于二型模糊神经网络的不确定混沌系统鲁棒性自适应控制()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
43卷
期数:
2019年04期
页码:
432-438
栏目:
出版日期:
2019-08-24

文章信息/Info

Title:
Interval type II fuzzy neural network control based robust adaptivefor the synchronization of uncertain chaotic systems
文章编号:
1005-9830(2019)04-0432-07
作者:
李洪梅高 媛陈向坚
江苏科技大学 计算机学院,江苏 镇江 212003
Author(s):
Li HongmeiGao YuanChen Xiangjian
School of Computer,Jiangsu University of Science and Technology,Zhenjiang 212003,China
关键词:
不确定性混沌系统 混沌同步 自适应控制 区间二型模糊神经网络 Lyapunov稳定
Keywords:
uncertain chaotic systems chaos synchronization adaptive control interval type Ⅱ fuzzy neural network Lyapunov stability
分类号:
TP391
DOI:
10.14177/j.cnki.32-1397n.2019.43.04.008
摘要:
该文提出的鲁棒的自适应区间二型模糊神经网络控制(RAITIIFNNC)系统由一个区间二型模糊神经网络识别器与一个鲁棒性控制器组成。识别器完成了对场地不确定性的在线评估,鲁棒控制器用来减小逼近错误,两者结合可以获得更好地跟踪与同步混沌系统。所有的参数学习算法来源于Lyapunov稳定理论以保证网络汇聚的同时有稳定同步的表现。算例分析证明:新系统在同步两个Lorenz混沌系统时具有更好的效率。
Abstract:
This paper proposes a robust adaptive interval type II fuzzy neural network control(RAITIIFNNC)to address the problem of controlled synchronization of a class of uncertain chaotic systems. The proposed RAITIIFNNC system is comprised of an interval type II fuzzy neural network identifier and a robust controller. The identifier is utilized for online estimation of the compound uncertainties. The robust controller is used to attenuate the effects of the approximation error so that the perfect tracking and synchronization of chaotic systems are achieved. All the parameter learning algorithms are derived based on Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. From the simulation example,to synchronize two Lorenz chaotic systems,the effectiveness of the proposed method has been verified.

参考文献/References:

[1] Pecora L M,Carroll T L. Synchronization in chaotic system[J]. Physical Review Letters,1990,64:821-830.
[2]Boccaletti S,Kurths J,Osipov G,et al. The synchronization of chaotic systems[J]. Physics Reports,2002,366(1-2):1-101.
[3]Zhang H G,Li M,Yang J,et al. Fuzzy model-based robust networked control for a class of nonlinear systems[J]. IEEE Transactions on Systems Man and Cybernetics-Part A Systems and Humans,2009,39(2):437-447.
[4]全永兵,张化光. 一类非线性系统的建模、辨识与控制研究[J]. 控制理论与应用,2001,9:349-354.
Quan Y B,Zhang H G. Modeling,identification and control of a class of nonlinear system[J]. Control Theory and Applications,2001,9:349-354.
[5]Tong S C,Li Y M. Observer-based fuzzy adaptive control for strict-feedback nonlinear system[J]. Fuzzy Sets and Systems,2009,160:1749-1764.
[6]Kadri M B. Disturbance rejection using fuzzy model free adaptive control(FMFAC)with adaptive conditional defuzzification threshold[J]. Journal of the Franklin Institute,2014,351(5):3013-3031.
[7]Li T S,Wang D,Feng G,et al. A DSC approach to robust adaptive NN tracking control for strict-feedback nonlinear system[J]. IEEE Transactions on Systems,Man,and Cybernetics,2010,40(3):915-927.
[8]陈沅涛,徐蔚鸿,吴佳英,等. 基于增量学习向量SVM方法的图像分割应用[J]. 南京理工大学学报,2014,38(1):6-11.
Chen R T,Xu W H,Wu J Y,et al. Image segmentation application based on incremental learning vector SVM algorithm[J]. Journal of Nanjing University of Science and Technology,2014,38(1):6-11.
[9]张磊,王冠,杨习贝,等. 八旋翼微型飞行器的自适应滑模控制器设计[J]. 南京理工大学学报,2018,42(1):33-39.
Zhang L,Wang G,Yang X B,et al. Designing adaptive sliding mode controller for an eight-rotor MAV[J]. Journal of Nanjing University of Science and Technology,2018,42(1):33-39.
[10]付思源,王华东. 和声搜索算法优化神经网络的无线网络室内定位[J]. 南京理工大学学报,2017,41(4):428-433.
Fu S Y,Wang H D. Indoor positioning of wireless network based on harmony search algorithm optimizing neural network[J]. Journal of Nanjing University of Science and Technology,2017,41(4):428-433.
[11]范永青,刘淳,王敏娟.一类不确定混沌系统的驱动响应同步控制[J]. 西安邮电大学学报,2019,24(1):63-67.
Fan Y Q,Liu C,Wang M J. Adaptive control of drive response synchronization for a uncertain class of chaotic systems[J]. Journal of Xi’an University of Posts and Telecommunications,2019,24(1):63-67.
[12]邓立为,宋申民. 基于输出反馈滑模控制的分数阶超混沌系统同步[J]. 自动化学报,2014,40(11):2420-2427.
Deng L W,Song S M. Synchronization of fractional order hyperchaotic systems based on output feedback sliding mode control[J]. Acta automatica Sinica,2014,40(11):2420-2427.
[13]耿宝亮,胡云安,李静,等. 控制增益为未知函数的不确定系统预设性能反演控制[J]. 自动化学报,2014,40(11):2521-2529.
Geng B L,Hu Y A,Li J,et al. Prescribed performance backstepping control of uncertain systems with unknown control gains[J]. Acta automatica Sinica,2014,40(11):2521-2529.
[14]杨兴明,李文静. 基于滑模控制器的四旋翼飞行器控制[J]. 合肥工业大学学报(自然科学版),2016,39(7):924-928.
Yang X M,Li W J. Four rotor aircraft control based on sliding mode controller[J]. Journal of Hefei University of Technology(Natural Science),2016,39(7):924-928.
[15]刘京,李洪文,邓永停.基于新型趋近律和扰动观测器的永磁同步电机滑模控制[J]. 工程科学学报,2017,39(6):933-944.
Liu J,Li H W,Deng Y T. PMSM sliding-mode control based on novel reaching law and disturbance observer[J]. Chinese Journal of Engineering,2017,39(6):933-944.
[16]Fard S P,Zainuddin Z. Interval type-2 fuzzy neural networks version of the Stone-Weierstrass theorem[J]. Neurocomputing,2011,74(14-15):2336-2343.
[17]廖传柱,张旦,江铭炎. 基于ABC-PCNN模型的图像分割[J]. 南京理工大学学报,2014,38(4):558-565.
Liao C Z,Zhang D,Jiang M Y. Image segmentation based on ABC-PCNN model[J]. Journal of Nanjing University of Science and Technology,2014,38(4):558-565.
[18]Chen C S,Lin W C. Self-adaptive interval type-2 neural fuzzy network control for PMLSM drives[J]. Expert Systems with Applications,2011,38(12):14679-14689.

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备注/Memo

备注/Memo:
收稿日期:2019-04-22 修回日期:2019-05-29
基金项目:国家自然科学基金(61572242); 江苏省研究生科研创新计划项目(KYCX19_1697)
作者简介:李洪梅(1978-),女,实验师,主要研究方向:模糊神经网络与智能控制,E-mail:maxzara@126.com。
引文格式:李洪梅,高媛,陈向坚. 基于二型模糊神经网络的不确定混沌系统鲁棒性自适应控制[J]. 南京理工大学学报,2019,43(4):432-438.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2019-09-30