搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于Weiner模型超混沌l系统的自适应辨识

赵益波 张秀再 孙心宇

引用本文:
Citation:

基于Weiner模型超混沌l系统的自适应辨识

赵益波, 张秀再, 孙心宇

Adaptive identification for hyperchaotic l system based on Weiner model

Zhao Yi-Bo, Zhang Xiu-Zai, Sun Xin-Yu
PDF
导出引用
  • 为了能实时而有效地辨识参数不确定的超混沌l系统,以便于对该系统进行控制或跟踪,本文提出了一种基于Wiener模型自适应分段线性(PWL)滤波器的超混沌系统辨识方法. Wiener模型的线性部分采用了线性横向滤波器,非线性部分用分段线性滤波器近似表示. 根据最小均方误差准则导出了滤波器参数更新算法,并进一步推导出算法的收敛性条件. 计算机仿真证实了该自适应滤波器辨识超混沌系统的有效性. 该方法不仅克服了自适应线性滤波器难以辨识出这类强非线性系统,而且比其他非线性自适应滤波器的计算复杂性低得多.
    In order to be able to identify the hyper-chaotic l system with uncertain parameters effectively in real time, so that hyper-chaotic system control and synchronization tracking can be applied, this paper presents a system identification method for the hyper-chaotic system based on Wiener model. The linear part of the Wiener model consists of linear transversal filters, while the nonlinear part is represented approximately by piecewise linear filters. According to the minimum mean square error criterion, the filter parameter updated algorithm is derived, and the convergence condition is also obtained. Simulation results confirm the effectiveness of the adaptive filter for the identification of hyper-chaotic systems. The presented method not only overcomes the difficulty to identify a strongly nonlinear system only by adaptive linear filters, but also have a lower computational complexity compared with other non-linear adaptive filters.
    • 基金项目: 江苏高校优势学科建设工程资助项目、南京信息工程大学科研基金(批准号:20110439)、优秀博士论文作者专项资金(批准号:27122)和国家自然科学基金(批准号:51077057)资助的课题.
    • Funds: Project in part supported by a Fund by the Priority Academic Program Development of Jiangsu Higher Education Institutions, Nanjing University of Information Science Nanjing University of Information Science Technology Research Foundation (Grant No. 20110439), the Outstanding Doctoral Dissertation Project of Special Funds (Grant No. 27122), and the National Natural Science Foundation of China, (Grant No. 51077057).
    [1]

    Wills A, Schn T B, Ljung L, Ninness B 2013 Automatica 49 70

    [2]

    Shafiee G, Arefi M M, Jahed-Motlagh M R, Jalali A A 2008 Chem. Eng. J. 143 282

    [3]
    [4]

    Peng J Z, Dubay R 2011 ISA Trans 50 588

    [5]
    [6]

    Silvina I B, Jos L F 2011 Comput. Chem. Eng. 35 2867

    [7]
    [8]

    Zhao Z J, Zheng X H, Shen L 2010 J. Circ. Syst. 15 11 (in Chinese) [赵知劲, 郑晓华, 沈雷 2010 电路与系统学报 15 11]

    [9]
    [10]

    Figueroa J L, Cousseau J E, Figueiredo R J P de 2004 Circ. Syst. Signal. Proc. 23 365

    [11]
    [12]

    Liu X F, Yang X Q, Zheng N N 2012 Neurocomputing 79 132

    [13]
    [14]

    Ma T D, Jiang W B, Fu J, Chai Y 2012 Acta Phys. Sin. 61 160506 (in Chinese)[马铁东, 江伟波, 浮洁, 柴毅 2012 物理学报 61 160506]

    [15]
    [16]

    Huang L L, Qi X 2013 Acta Phys. Sin. 62 080507 (in Chinese)[黄丽莲, 齐雪 2013 物理学报 62 080507]

    [17]
    [18]

    Yang J, Sun Q Y, Yang D S 2012 Acta Phys. Sin. 61 200511 (in Chinese)[杨珺, 孙秋野, 杨东升 2012 物理学报 61 200511]

    [19]
    [20]
    [21]

    Yang D S, Liu Z W, Zhao Y, Liu Z B 2012 Chin. Phys. B 21 040503

    [22]
    [23]

    Xu Y H, Li B, Zhou W N, Fang J A 2012 Nonlinear. Dynam. 70 289

    [24]
    [25]

    Luo R Z, Wang Y L 2012 Chaos. 22 023109

    [26]
    [27]

    Li D, Deng L M, Du Y X, Yang Y 2012 Acta Phys. Sin. 61 050502 (in Chinese)[李东, 邓良明, 杜永霞, 杨媛 2012 物理学报 61 050502]

    [28]
    [29]

    Zhang H L, Song L L 2013 Acta Phys. Sin. 62 190508 (in Chinese)[张宏立, 宋莉莉 2013 物理学报 62 190508]

    [30]
    [31]

    Zhu D R, Liu C X, Yan B N 2012 Chin. Phys. B 21 090509

    [32]

    Gu W D, Sun Z Y, Wu X M, Yu C B 2013 Chin. Phys. B 22 090203

    [33]
    [34]

    Haykin S 2002 Adaptive filter theory (New York: Pearson Education)

    [35]
    [36]

    Zheng C D, Shan Q H, Zhang H G, Wang Z S 2013 IEEE Trans. Neural. Networks. Learning. Syst. 24 800

    [37]
    [38]
    [39]

    Chen A M, Junan Lu J N, L J H, Yu S M 2006 Phys. A 364 103

    [40]

    Chua L O, Deng A C 1988 IEEE Trans. Circ. Syst. 35 101

    [41]
    [42]
    [43]

    Julian P 1999 High level canonical piecewise linear representation: Theory and applications. (Ph. D. thesis in Systems Control, Universidad Nacional del Sur, UMI Dissertation Services)

  • [1]

    Wills A, Schn T B, Ljung L, Ninness B 2013 Automatica 49 70

    [2]

    Shafiee G, Arefi M M, Jahed-Motlagh M R, Jalali A A 2008 Chem. Eng. J. 143 282

    [3]
    [4]

    Peng J Z, Dubay R 2011 ISA Trans 50 588

    [5]
    [6]

    Silvina I B, Jos L F 2011 Comput. Chem. Eng. 35 2867

    [7]
    [8]

    Zhao Z J, Zheng X H, Shen L 2010 J. Circ. Syst. 15 11 (in Chinese) [赵知劲, 郑晓华, 沈雷 2010 电路与系统学报 15 11]

    [9]
    [10]

    Figueroa J L, Cousseau J E, Figueiredo R J P de 2004 Circ. Syst. Signal. Proc. 23 365

    [11]
    [12]

    Liu X F, Yang X Q, Zheng N N 2012 Neurocomputing 79 132

    [13]
    [14]

    Ma T D, Jiang W B, Fu J, Chai Y 2012 Acta Phys. Sin. 61 160506 (in Chinese)[马铁东, 江伟波, 浮洁, 柴毅 2012 物理学报 61 160506]

    [15]
    [16]

    Huang L L, Qi X 2013 Acta Phys. Sin. 62 080507 (in Chinese)[黄丽莲, 齐雪 2013 物理学报 62 080507]

    [17]
    [18]

    Yang J, Sun Q Y, Yang D S 2012 Acta Phys. Sin. 61 200511 (in Chinese)[杨珺, 孙秋野, 杨东升 2012 物理学报 61 200511]

    [19]
    [20]
    [21]

    Yang D S, Liu Z W, Zhao Y, Liu Z B 2012 Chin. Phys. B 21 040503

    [22]
    [23]

    Xu Y H, Li B, Zhou W N, Fang J A 2012 Nonlinear. Dynam. 70 289

    [24]
    [25]

    Luo R Z, Wang Y L 2012 Chaos. 22 023109

    [26]
    [27]

    Li D, Deng L M, Du Y X, Yang Y 2012 Acta Phys. Sin. 61 050502 (in Chinese)[李东, 邓良明, 杜永霞, 杨媛 2012 物理学报 61 050502]

    [28]
    [29]

    Zhang H L, Song L L 2013 Acta Phys. Sin. 62 190508 (in Chinese)[张宏立, 宋莉莉 2013 物理学报 62 190508]

    [30]
    [31]

    Zhu D R, Liu C X, Yan B N 2012 Chin. Phys. B 21 090509

    [32]

    Gu W D, Sun Z Y, Wu X M, Yu C B 2013 Chin. Phys. B 22 090203

    [33]
    [34]

    Haykin S 2002 Adaptive filter theory (New York: Pearson Education)

    [35]
    [36]

    Zheng C D, Shan Q H, Zhang H G, Wang Z S 2013 IEEE Trans. Neural. Networks. Learning. Syst. 24 800

    [37]
    [38]
    [39]

    Chen A M, Junan Lu J N, L J H, Yu S M 2006 Phys. A 364 103

    [40]

    Chua L O, Deng A C 1988 IEEE Trans. Circ. Syst. 35 101

    [41]
    [42]
    [43]

    Julian P 1999 High level canonical piecewise linear representation: Theory and applications. (Ph. D. thesis in Systems Control, Universidad Nacional del Sur, UMI Dissertation Services)

  • [1] 王跃钢, 文超斌, 杨家胜, 左朝阳, 崔祥祥. 基于无模型方法的混沌系统自适应控制. 物理学报, 2013, 62(10): 100504. doi: 10.7498/aps.62.100504
    [2] 周武杰, 郁梅, 禹思敏, 蒋刚毅, 葛丁飞. 一种基于超混沌系统的立体图像零水印算法. 物理学报, 2012, 61(8): 080701. doi: 10.7498/aps.61.080701
    [3] 马铁东, 江伟波, 浮洁, 薛方正. 基于改进脉冲控制方法的超混沌系统同步. 物理学报, 2012, 61(10): 100507. doi: 10.7498/aps.61.100507
    [4] 李春来, 禹思敏. 一个新的超混沌系统及其自适应追踪控制. 物理学报, 2012, 61(4): 040504. doi: 10.7498/aps.61.040504
    [5] 张晓丹, 崔丽娟. 一类四维超混沌系统的界及同步的研究. 物理学报, 2011, 60(11): 110511. doi: 10.7498/aps.60.110511
    [6] 刘扬正, 林长圣, 王忠林. 新的切换四涡卷超混沌系统及其电路实现. 物理学报, 2010, 59(12): 8407-8413. doi: 10.7498/aps.59.8407
    [7] 闵富红, 王恩荣. 超混沌Qi系统的错位投影同步及其在保密通信中的应用. 物理学报, 2010, 59(11): 7657-7662. doi: 10.7498/aps.59.7657
    [8] 王兴元, 孟娟. 基于Takagi-Sugeno模糊模型的超混沌系统自适应投影同步及参数辨识. 物理学报, 2009, 58(6): 3780-3787. doi: 10.7498/aps.58.3780
    [9] 胡国四. 超混沌吸引子的翼倍增方案. 物理学报, 2009, 58(12): 8139-8145. doi: 10.7498/aps.58.8139
    [10] 闵富红, 余杨, 葛曹君. 超混沌分数阶Lü系统电路实验与追踪控制. 物理学报, 2009, 58(3): 1456-1461. doi: 10.7498/aps.58.1456
    [11] 唐良瑞, 李静, 樊冰. 一个新四维自治超混沌系统及其电路实现. 物理学报, 2009, 58(3): 1446-1455. doi: 10.7498/aps.58.1446
    [12] 刘扬正, 姜长生. 关联可切换超混沌系统的构建与特性分析. 物理学报, 2009, 58(2): 771-778. doi: 10.7498/aps.58.771
    [13] 王兴元, 孟 娟. 超混沌系统的广义同步化. 物理学报, 2007, 56(11): 6288-6293. doi: 10.7498/aps.56.6288
    [14] 刘扬正, 姜长生, 林长圣, 孙 晗. 四维切换超混沌系统. 物理学报, 2007, 56(9): 5131-5135. doi: 10.7498/aps.56.5131
    [15] 王兴元, 武相军. 不确定Chen系统的参数辨识与自适应同步. 物理学报, 2006, 55(2): 605-609. doi: 10.7498/aps.55.605
    [16] 甘建超, 肖先赐. 基于相空间邻域的混沌时间序列自适应预测滤波器(Ⅰ)线性自适应滤波. 物理学报, 2003, 52(5): 1096-1101. doi: 10.7498/aps.52.1096
    [17] 甘建超, 肖先赐. 基于相空间邻域的混沌时间序列自适应预测滤波器(Ⅱ)非线性自适应滤波. 物理学报, 2003, 52(5): 1102-1107. doi: 10.7498/aps.52.1102
    [18] 韦保林, 罗晓曙, 汪秉宏, 全宏俊, 郭维, 傅金阶. 一种基于三阶Volterra滤波器的混沌时间序列自适应预测方法. 物理学报, 2002, 51(10): 2205-2210. doi: 10.7498/aps.51.2205
    [19] 张家树, 肖先赐. 用于混沌时间序列自适应预测的一种少参数二阶Volterra滤波器. 物理学报, 2001, 50(7): 1248-1254. doi: 10.7498/aps.50.1248
    [20] 张家树, 肖先赐. 用一种少参数非线性自适应滤波器自适应预测低维混沌时间序列. 物理学报, 2000, 49(12): 2333-2339. doi: 10.7498/aps.49.2333
计量
  • 文章访问数:  4824
  • PDF下载量:  500
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-10-14
  • 修回日期:  2014-03-13
  • 刊出日期:  2014-07-05

/

返回文章
返回