Volume 30 Issue 2
Apr.  2021
Turn off MathJax
Article Contents
SUN Xiaohui, WEN Chenglin, WEN Tao, “A Novel Step-by-Step High-Order Extended Kalman Filter Design for a Class of Complex Systems with Multiple Basic Multipliers,” Chinese Journal of Electronics, vol. 30, no. 2, pp. 313-321, 2021, doi: 10.1049/cje.2021.02.005
Citation: SUN Xiaohui, WEN Chenglin, WEN Tao, “A Novel Step-by-Step High-Order Extended Kalman Filter Design for a Class of Complex Systems with Multiple Basic Multipliers,” Chinese Journal of Electronics, vol. 30, no. 2, pp. 313-321, 2021, doi: 10.1049/cje.2021.02.005

A Novel Step-by-Step High-Order Extended Kalman Filter Design for a Class of Complex Systems with Multiple Basic Multipliers

doi: 10.1049/cje.2021.02.005
Funds:

he National Natural Science Foundation of China 61751304

he National Natural Science Foundation of China 61806064

he National Natural Science Foundation of China 6193301

he National Natural Science Foundation of China 61703385

he National Natural Science Foundation of China U1664264

Science and Technology Project of China Electric Power Research Institute SGHB0000KXJS1800375

More Information
  • Author Bio:

    SUN Xiaohui   was born in 1993. She received B.E. degree from Harbin University of Science and Technology. She studied for a M.S. degree and a Ph.D. in Hangzhou Dianzi University in 2016 and 2018, respectively, and is currently a Ph.D. candidate. Her research interest is filter design. (Email: sun_xh1993@163.com)

    WEN Chenglin   was born in 1963. He graduated from Henan University in 1986, graduated from Zhengzhou University with a M.S. degree in 1993 and received a Ph.D. from Northwestern Polytechnical University 1999. He went out of the postdoctoral mobile station of Control Science and Engineering of Tsinghua University in 2002. He is a professor of Hangzhou Dianzi University and Guangdong University of Petrochemical Technology. His research interests include information fusion and target detection, fault diagnosis and active security control, deep learning and optimization decision-making systems, cyberspace security and attack detection and positioning.(Email: wencl@hdu.edu.cn)

  • Corresponding author: WEN Tao   (corresponding author) received the B.E. degree in computer science from Hangzhou Dianzi University in 2011, the M.S. degree from the University of Bristol, Bristol, U.K. in 2013, and the Ph.D. degree from the Birmingham Centre for Railway Research and Education, University of Birmingham, Birmingham, U.K. in 2018. He currently works in the School of Electronic and Information Engineering, Beijing Jiaotong University. His research interests include CBTC system optimization, railway signaling simulation, railway dependability improvement, wireless signal processing, and digital filter research (Email: wentao@bjtu.edu.cn)
  • Received Date: 2020-08-11
  • Accepted Date: 2020-10-28
  • Publish Date: 2021-03-01
  • A novel step-by-step linearization highorder Extended Kalman filter SH-EKF is designed for a class of nonlinear systems composed of linear functions and the product of several separable basic functions. The basic functions in the state and measurement models are defined as latent variables; the state and measurement models are equivalently formulated into pseudo-linear models based on the combination of the original variable and the latent variables; latent variables are regarded as new variables, and a dynamic linear model between each latent variable and other latent variables with original state is established; the measurement model is rewritten into the first-order linear product form between the current state and each latent variable; latent variables are solved by Kalman filter step by step, and a stepwise linearized high-order extended Kalman filter is designed. Illustration examples are presented to demonstrate the effectiveness of the new algorithm.
  • loading
  • [1]
    T. Wen, Q.B. Ge, X. Lyu, et al., "A cost-effective wireless network migration planning method supporting high-security enabled railway data communication systems", Journal of the Franklin Institute, Vol. 35, No. 6, pp. 114-121, 2019. http://www.sciencedirect.com/science/article/pii/S0016003219300936
    [2]
    T. Wen, Constantinou. C, L. Chen, Z. Tian and C. Roberts. "Access point deployment optimization in CBTC data communication system", IEEE Transactions on Intelligent Transportation Systems, Vol. 19, No. 6, pp. 1985-1995, 2018. doi: 10.1109/TITS.2017.2747759
    [3]
    C.B. Wen, Z.D. Wang, Q.Y. Liu, et al., "Recursive distributed filtering for a class of state-saturated systems with fading measurements and quantization effects", IEEE Transactions on Systems, Man and Cybernetics: Systems, Vol. 48, No. 6, pp. 930-941, 2018. doi: 10.1109/TSMC.2016.2629464
    [4]
    T. Wen, C.B. Wen, C. Roberts, et al., "Distributed filtering for a class of discrete-time systems over wireless sensor networks", Journal of the Franklin Institute, Vol. 357, No. 5, pp. 67-72, 2020. http://www.sciencedirect.com/science/article/pii/S0016003220300892
    [5]
    C.B. Wen, Z.D. Wang, J. Hu, et al., "Alsaadi. Recursive filtering for state-saturated systems with randomly occurring nonlinearities and missing measurements", International Journal of Robust and Nonlinearity Control, Vol. 28, No. 1, pp. 1715-1727, 2018. doi: 10.1002/rnc.3992
    [6]
    Wiener N. The Extrapolation, Interpolation and Smooth of Stationary Time Series, The MIT Press, New York, USA, pp. 1-239, 1942.
    [7]
    C.L. Wen, X.S. Cheng, D. X Xu, et al., "Filter design based on characteristic functions for one class of multi-dimensional nonlinear non-Gaussian systems", Automatica, Vol. 82, pp. 171-180, 2017. doi: 10.1016/j.automatica.2017.03.041
    [8]
    R.E. Kalman, "A new approach to linear filter and prediction problem", IEEE Transactions of the ASME Journal of Basic Engineering, Vol. 82, pp. 35-45, 1960. doi: 10.1115/1.3662552
    [9]
    S.J. Qiao, N. Han and X.W. Zhu, "A Dynamic trajectory prediction algorithm based on Kalman filter", Acta Electronica Sinica, Vol. 26, No. 2, pp. 418-423, 2018. (in Chinese)
    [10]
    Y. Sunahara and K. Yamashita, "An approximate method of state estimation for nonlinear dynamical systems with state-dependent noise", International Journal of Control, Vol. 11, No. 4, pp. 957-972, 1970. doi: 10.1080/00207177008905976
    [11]
    D.H. Zhou, Y.G. Xi and Z.J. Zhang, "A Suboptimal Multiple Fading Extended Kalman Filter", ACTA Automatica Sinica, Vol. 17, no. 6, pp. 689-695, 1991. (in Chinese) http://www.cqvip.com/QK/90250X/19916/687639.html
    [12]
    S.J. Julier and J.K. Uhlmann, "Unscented filtering and nonlinear estimation", Proceedings of the IEEE, Vol. 92, No. 3, pp. 401-422, 2004. doi: 10.1109/JPROC.2003.823141
    [13]
    C.L. Wen, Q.B. Ge, X.S. Cheng, et al., "Filters design based on multiple characteristic functions for the grinding process cylindrical workpieces", IEEE Transactions on Industrial Electronics, Vol. 64, No. 6, pp. 4671-4679, 2017 doi: 10.1109/TIE.2017.2668980
    [14]
    I. Arasaratnam and S. Haykin, "Cubature Kalman filters", IEEE Transactions on Automatic Control, Vol. 54, No. 6, pp. 1254-1269, 2009. doi: 10.1109/TAC.2009.2019800
    [15]
    I. Arasaratnam and S. Haykin, "Square-root quadrature Kalman filtering", IEEE Transactions on Signal Processing, Vol. 56, No. 6, pp. 2589-2593, 2008. doi: 10.1109/TSP.2007.914964
    [16]
    K. Kowalski and W.H. Steeb, "Nonlinear dynamical systems and Carleman linearization", World Scientific, Singapore, 1991. doi: 10.1142/1347
    [17]
    A. Germani, C. Manes and P. Palumbo, "Polynomial extended Kalman filter", IEEE Transactions on Automatic Control, Vol. 50, No. 12, pp. 2059-2064, 2005. doi: 10.1109/TAC.2005.860256
    [18]
    Y. Liu, Z.D. Wang, X. He, et al., "Filtering and fault detection for nonlinear systems with polynomial approximation", Automatica, Vol. 54, pp. 348-359, 2015. doi: 10.1016/j.automatica.2015.02.022
    [19]
    A. Germani, C. Manes and P. Palumbo, "Polynomial extended Kalman filtering for discrete-time nonlinear stochastic systems", In Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, Hawaii USA, pp. 886-891, 2003.
    [20]
    A. Germani, C. Manes and P. Palumbo, "Filtering of stochastic nonlinear differential systems via a Carleman approximation approach", IEEE Transactions on Automatic Control, Vol. 52, No. 11, pp. 2166-2172, 2007. doi: 10.1109/TAC.2007.908347
    [21]
    X. Guo, L.L. Sun, T. Wen, et al., "Adaptive transition probability matrix-based parallel IMM algorithm", IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 19, No. 14, pp. 1-10, 2019. http://ieeexplore.ieee.org/document/8747402
    [22]
    G. Mavelli and P. Palumbo, "The carleman approximation approach to solve a stochastic nonlinear control problem", IEEE Transactions on Automatic Control, Vol. 55, No. 4, pp. 976-982, 2010. doi: 10.1109/TAC.2010.2041611
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(3)

    Article Metrics

    Article views (701) PDF downloads(38) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return