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基于多核最小二乘支持向量机的永磁同步电机混沌建模及其实时在线预测

陈强 任雪梅

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基于多核最小二乘支持向量机的永磁同步电机混沌建模及其实时在线预测

陈强, 任雪梅

Chaos modeling and real-time online prediction of permanent magnet synchronous motor based on multiple kernel least squares support vector machine

Chen Qiang, Ren Xue-Mei
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  • 提出了多核最小二乘支持向量机的永磁同步电机混沌系统建模方法. 通过不同核函数的线性加权组合构造新的等价核,降低建模精度对核函数及其参数选择的依赖性. 理论上给出多核最小二乘支持向量机回归参数和模型输出值的求解方法. 采用关联积分计算方法对永磁同步电机混沌系统进行相空间重构,以窗式移动的在线学习方式对重构后的永磁同步电机混沌序列进行一步和多步实时在线预测,并讨论了不同测量噪声对该方法的影响. 仿真结果表明,该方法能有效提高永磁同步电机混沌系统的建模精度,具有良好的抗噪能力.
    A multiple kernel least squares support vector machine (MK-LSSVM) modeling method is proposed for the chaos of permanent magnet synchronous motor (PMSM). An equivalent kernel is built by linear-weighted combination of multi kernels to reduce the dependence of modeling accuracy on kernel function and parameters. The solutions of regression parameters and MK-LSSVM output are given in theory. C-C method is employed for the phase space reconstruction of PMSM chaos, then one-step and multi-step real-time online prediction of reconstructed chaotic series are investigated based on moving window learning method. The effect of different measurement noises on the proposed method is discussed. Simulations show that the proposed method can enhance the modeling accuracy and have strong anti-noise capability.
    • 基金项目: 国家自然科学基金(批准号:60474033和60974046)资助的课题.
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    [2]

    [2]Rahman M A, Zhou P 1996 IEEE Trans. Ind. Electron. 43 256

    [3]

    [3]Ooshima M, Chiba A 2004 IEEE Trans. En. Convers. 19 569

    [4]

    [4]Li Z, Park J B, Joo Y H, Zhang B, Chen G 2002 IEEE Trans. Circ. Syst. 1 49 383

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    [5]Jing Z, Yu C, Chen G 2004 Chaos, Solitons. Fract. 22 831

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    ]Wang Y S, Sun J, Wang C J, Fan H D 2008 Acta Phys. Sin. 57 6120 (in Chinese) [王永生、孙谨、王昌金、范洪达 2008 物理学报 57 6120]

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    ]Zhang J F, Hu S S 2007 Acta Phys. Sin. 56 713 (in Chinese) [张军峰、胡寿松 2007 物理学报 56 713]

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    ]Vapnik V 1995 The Nature of Statistical Learning Theory (Singapore: World Scientific)

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    ]Suykens J A K, Gestel T V, Brabanter, Moor B D, Vandewalle J 2002 Least Squares Support Vector Machines (Singapore: World Scientific)

    [14]

    ]Ye M Y, Wang X D, Zhang H R 2005 Acta Phys. Sin. 54 2568 (in Chinese) [叶美盈、汪晓东、张浩然 2005 物理学报 54 2568]

    [15]

    ]Guo Z K, Song Z Q, Mao J Q 2009 Contr. Decis. 24 145 (in Chinese)[郭振凯、宋召青、毛剑琴 2009控制与决策 24 145]

    [16]

    ]Zien A, Ong C S 2007 Proceeding of the 24th International Conference on Machine Learning Oregon, USA, June 20—24 2007 P1191

    [17]

    ]Hu M, Chen Y, Kwok J T 2009 IEEE Trans. Neural Network 20 827

    [18]

    ]Zhang J F, Hu S S 2008 Acta Phys. Sin. 57 2708 (in Chinese) [张军峰、胡寿松 2008 物理学报 57 2708]

    [19]

    ]Takens F 1981 Lecture Notes in Mathematics (Berlin: Springer) p366

    [20]

    ]Kantz H, Schreiber T 1997 Nonlinear Time Series Analysis (Cambridge: Cambridge University Press)

    [21]

    ]Fraster A M, Swinney H L 1986 Phys. Rev. A 33 1134

    [22]

    ]Kugiurmtzis D 1996 Physica D 28 13

    [23]

    ]Kim H S, Eykholt R, Salas J D 1999 Physica D 127 48

    [24]

    ]Kuhn H W, Tucker A W 1951 Proceedings of 2nd Berkeley Symposium (Berkeley: University of California Press) p481

    [25]

    ]Mercer J 1909 Philos. Trans. Roy. Soc. 209 415

  • [1]

    [1]Pillay P, Krishnan R 1989 IEEE Trans Ind. Appl. 25 265

    [2]

    [2]Rahman M A, Zhou P 1996 IEEE Trans. Ind. Electron. 43 256

    [3]

    [3]Ooshima M, Chiba A 2004 IEEE Trans. En. Convers. 19 569

    [4]

    [4]Li Z, Park J B, Joo Y H, Zhang B, Chen G 2002 IEEE Trans. Circ. Syst. 1 49 383

    [5]

    [5]Jing Z, Yu C, Chen G 2004 Chaos, Solitons. Fract. 22 831

    [6]

    [6]Xue W 2009 Acta Phys. Sin. 58 8146 (in Chinese) [薛薇 2009 物理学报 58 8146]

    [7]

    [7]Zhang B, Li Z, Mao Z Y 2002 Cont. Theory Appl. 19 841 (in Chinese) [张波、李忠、毛宗源 2002控制理论与应用 19 841]

    [8]

    [8]Zhang J M, Wang K J 2007 Proc. Chin. Soc. Electr. Engng. 27 7 (in Chinese) [张建民、王科俊 2007中国电机工程学报 27 7]

    [9]

    [9]Tan W, Wang Y N, Liu Z R, Zhou S W 2003 Acta Phys. Sin. 52 795 (in Chinese) [谭文、王耀南、刘祖润、周少武 2003 物理学报52 795]

    [10]

    ]Wang Y S, Sun J, Wang C J, Fan H D 2008 Acta Phys. Sin. 57 6120 (in Chinese) [王永生、孙谨、王昌金、范洪达 2008 物理学报 57 6120]

    [11]

    ]Zhang J F, Hu S S 2007 Acta Phys. Sin. 56 713 (in Chinese) [张军峰、胡寿松 2007 物理学报 56 713]

    [12]

    ]Vapnik V 1995 The Nature of Statistical Learning Theory (Singapore: World Scientific)

    [13]

    ]Suykens J A K, Gestel T V, Brabanter, Moor B D, Vandewalle J 2002 Least Squares Support Vector Machines (Singapore: World Scientific)

    [14]

    ]Ye M Y, Wang X D, Zhang H R 2005 Acta Phys. Sin. 54 2568 (in Chinese) [叶美盈、汪晓东、张浩然 2005 物理学报 54 2568]

    [15]

    ]Guo Z K, Song Z Q, Mao J Q 2009 Contr. Decis. 24 145 (in Chinese)[郭振凯、宋召青、毛剑琴 2009控制与决策 24 145]

    [16]

    ]Zien A, Ong C S 2007 Proceeding of the 24th International Conference on Machine Learning Oregon, USA, June 20—24 2007 P1191

    [17]

    ]Hu M, Chen Y, Kwok J T 2009 IEEE Trans. Neural Network 20 827

    [18]

    ]Zhang J F, Hu S S 2008 Acta Phys. Sin. 57 2708 (in Chinese) [张军峰、胡寿松 2008 物理学报 57 2708]

    [19]

    ]Takens F 1981 Lecture Notes in Mathematics (Berlin: Springer) p366

    [20]

    ]Kantz H, Schreiber T 1997 Nonlinear Time Series Analysis (Cambridge: Cambridge University Press)

    [21]

    ]Fraster A M, Swinney H L 1986 Phys. Rev. A 33 1134

    [22]

    ]Kugiurmtzis D 1996 Physica D 28 13

    [23]

    ]Kim H S, Eykholt R, Salas J D 1999 Physica D 127 48

    [24]

    ]Kuhn H W, Tucker A W 1951 Proceedings of 2nd Berkeley Symposium (Berkeley: University of California Press) p481

    [25]

    ]Mercer J 1909 Philos. Trans. Roy. Soc. 209 415

计量
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  • PDF下载量:  1195
  • 被引次数: 0
出版历程
  • 收稿日期:  2009-07-31
  • 修回日期:  2009-09-21
  • 刊出日期:  2010-02-05

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