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电子学报  2014 

基于EMD与LS-SVM的网络控制系统时延预测方法

DOI: 10.3969/j.issn.0372-2112.2014.05.006, PP. 868-874

Keywords: 网络控制系统,经验模式分解,最小二乘支持向量机,时延,预测

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Abstract:

为了提高基于Internet的网络控制系统中随机时延的预测精度,提出了基于经验模式分解(empiricalmodedecomposition,EMD)与最小二乘支持向量机(LeastSquaredSupportVectorMachines,LS-SVM)的一步时延预测方法.首先利用EMD将时延序列分解成若干个本征模式函数分量,分解后的分量去除了原始时延序列的长相关性,同时突出时延序列不同的局部特征.然后根据各个分量的变化规律,选择不同的LS-SVM模型分别进行预测.最后将各分量的预测值叠加得到最终的预测值.仿真结果表明本文方法具有较高的预测精度.

References

[1]  N Sadeghzaedh,A Afshar,M B Menhaj.An MLP neural network for time delay prediction in networked control systems[A].2008 Chinese Control and Decision Conference[C].Yangtai,China:IEEE Press, 2008.5314-5318.
[2]  曹庆璞,董淑福,罗骞.网络时延的混沌性分析及预测[J].计算机技术与发展,2010,20(4):43-46. Cao Qing-pu,Dong Shu-fu,Luo Yun-qian.Chaotic analysis and prediction of Internet time-delay[J].Computer Technology and Development,2010,20(4):43-46.(in Chinese)
[3]  王永骥,杨业,吴浩.基于SVM的Internet的网络时延分步及预测[J].华中科技大学学报,2006,34(6):89-91. Wang Yong-ji,Yang Ye,Wu Hao.The analysis and prediction of Internet time-delay based on support vector machines[J].J.Huazhong Univ of Sci & Tech(Nature Science Edition),2006,34(6):89-91.(in Chinese)
[4]  李春茂,肖建,张.网络控制系统的时延估计和自适应预测控制[J].西南交通大学学报,2007,42(2):175-180. Li Chun-mao,Xiao Jian,Zhang Yue.Time delay estimation and adaptive control of networked control systems[J].Journal of Southwest Jiaotong University,2007,42(2):175-180.(in Chinese)
[5]  A Erramilli,M Roughan,D Veitch,et al.Self-similar traffic and network dynamics[J].Proc of the IEEE,2002,90(5):800-819.
[6]  李玉清,方华京,朱菲.随机时延网络化控制系统的自适应预测控制[J].华中科技大学学报(自然科学版),2009,37(1):292-296. Li Yu-qing,Fang Hua-jing,Zhu Fei.Adaptive predicted control of networked control system with random delays[J].J Huazhong Univ of Sci & Tech(Natural Science Edition),2009,37(1):292-296.(in Chinese)
[7]  时为国,邵成,孙正阳.基于AR模型时延预测的改进GPC网络控制算法[J].控制与决策,2012,27(3):477-480. Shi Wei-guo,Shao Cheng,Sun Zheng-yang.Improved GPC network-control algorithm based on AR model time-delay prediction[J].Control and Decision,2012,27(3):477-480.(in Chinese)
[8]  M Yang,J F Ru,X R Li,et al.Predicting internet end-to-end delay:a multiple-model approach[A].Proceedings of the IEEE NFCOM[C].Miami,F L,USA:IEEE Press,2005.3047-3051.
[9]  宋杨,涂小敏,费敏锐.基于FARIMA模型的Internet时延预测[J].仪器仪表学报,2012,33(4):757-763. SONG Yang,TU Xiao-min,FEI Min-rui.Internet time-delay prediction based on FARIMA model[J].Chinese Journal of Scientific Instrument,2012,33(4):757-763.(in Chinese)
[10]  H Y Li,H Wang,C Gui.Internet time-delayprediction based on autoregressive and neural network model[A].2006 International Conference on Communications,Circuits and Systems[C].Guilin,China:IEEE Press,2006.1758-1761.
[11]  D Liu,J H Du,Y Zhao,et al.Study on the time-delay of Internet-based industry process control system[A].Proc.of the Fifth World Conference on Intelligent Control and Automation[C].Hangzhou,China:IEEE Press,2002.1376- 1380.
[12]  B Rahmani,A H D Markazi,N Mozayani.Real time prediction of time delays in a networked control system[A].2008 3rd International Symposium on Communications,Control and Signal Processing[C].St.Julians,Malta:IEEE Press,2008.1242-1245.
[13]  T Karagiannis,M Molle,M Faloutsos.Long-range dependence:Ten years of internet traffic modeling[J].IEEE Internet Computing,2004,8(5):57-64.
[14]  S H Wang,B G Xu,Q Y Wang.Delays analysis for teleportation over Internet and smith predictor with adaptive time-delay control[A].Proc of the IEEE International Conference on Robotics and Biomimetics[C].Piscataway,NJ,USA:IEEE Press,2005.664-669.
[15]  X H Fu,X Fu.A predictive algorithm for time delay internet network[A].IEEE International Conference on Electronics,Communications and Control[C].Ningbo,China:IEEE Press,2011.666-669.
[16]  J P Zhao,X W Gao.Time-delay analysis and estimation of internet-based robot teleoperation system[A].21st Chinese Control and Decision Conference[C].Guilin,China:IEEE Press,2009.4643-4646.
[17]  N E Huang,Z Shen,S Long,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society of London Series A,1998,454:903-995.
[18]  彭喜元,王军,彭宇.一种新型时间序列多分辨预测模型研究[J].电子学报,2007,35(11): 2146-2149. Peng Xi-yuan,Wang Jun,Peng yu.A novel multi-scale predictor for complex time series[J].Acta Electronica Sinica,2007,35(11):2146-2149.(in Chinese)
[19]  王军,彭喜元,彭宇.一种新型复杂时间序列实时预测模型研究[J].电子学报,2006,34(12A):2391-2394. Wang Jun,Peng Xi-yuan,Peng Yu.A novel real time predictor for complex time series[J].Acta Electronica Sinica,2006,34(12A):2391-2394.(in Chinese)
[20]  J A K Suykens,L Lukas,J Vandewalle.Least squares support vector machine classifiers[J].Neural processing Letters,1999,9(3):293-300.
[21]  胡志国,张大陆,侯翠平,等.基于随机神经网络的多步网络时延预测模型[J].计算机科学,2009,36(7):85-88. [LL]Hu Zhi-guo,Zhang Da-lu,Hou Cui-ping,et al.Multi-step network delay prediction model based on RNN[J].Computer Science,2009,36(7):85-88.(in Chinese)
[22]  高波,张钦宇,梁永生,等.基于EMD及ARMA的自相似网络流量预测[J].通信学报,2011,32(4):47-56. Gao Bo,Zhang Qin-yu,Liang Yong-sheng,et al.Predicting self-similar networking traffic based on EMD and ARMA[J].Journal on Communications,2011,32(4):47-56.(in Chinese)

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