Welcome to Journal of Beijing Institute of Technology
Advance Search
Volume 25Issue 1
.
Turn off MathJax
Article Contents
Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2016> 25(1): 108-114
FENG Lu, DENG Zhi-hong, WANG Bo, WANG Shun-ting. Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2016, 25(1): 108-114. doi: 10.15918/j.jbit1004-0579.201625.0116
Citation: FENG Lu, DENG Zhi-hong, WANG Bo, WANG Shun-ting. Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2016, 25(1): 108-114.doi:10.15918/j.jbit1004-0579.201625.0116
shu

Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements

doi:10.15918/j.jbit1004-0579.201625.0116

  • School of Automation, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2014-09-19
    Abstract
  • A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements. The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution, the commonest cases in engineering, such that the expectation of the measurements could be utilized during the iteration process. To consider the uncertainties in the system model, an upper-bound for the estimation error covariance was obtained since its real value was unaccessible. Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided. Simulations are presented to illustrate the effectiveness of the proposed approach.
    • FullText(HTML)
  • loading
    • References (25)
  • [1]
    Du Dongsheng, Jiang Bin, Shi Peng, et al. H ∞filter of discrete-time switched systems with state delays via switched Lyapunov function approach[J]. IEEE Transactions on Automatic Control, 2007,52(8):1520-1525.
    [2]
    Gao Huijun, Meng Xiangyu, Chen Tongwen. A new design of robust H 2filters for uncertain systems[J]. Systems & Control Letters, 2008,57(7):585-593.
    [3]
    Shi Peng, Mahmoud M, Nguang S K, et al. Robust filter for jumping systems with mode-dependent delays[J]. Signal Processing, 2006,86(1):140-152.
    [4]
    Wang Zidong, Liu Yurong, Liu Xiaohui. H ∞filter for uncertain stochastic time-delay systems with sector-bounded nonlinearities[J]. Automatica, 2008,44(5):1268-1277.
    [5]
    Kassel R J, Baxa E G, Jr. The effect of missing data on the steady-state performance of an alpha, beta tracking filter[C]//Proceedings of the Twentieth Southeastern Symposium on System Theory, Washington, D.C., USA, 1988:526-529.
    [6]
    Rosen Y, Porat B. Optimal ARMA parameter estimation based on the sample covariances for data with missing observations[J]. IEEE Transactions on Information Theory, 1989,35(2):342-349.
    [7]
    Savkin A V, Petersen I R, Reza Moheimani S O. Model validation and state estimation for uncertain continuous-time systems with missing discrete-continuous data[J]. Computers & Electrical Engineering, 1999,25(1):29-43.
    [8]
    Yang Fuwen, Wang Zidong, Hung Y S. Robust Kalman filter for discrete time-varying uncertain systems with multiplicative noises[J]. IEEE Transactions on Automatic Control, 2002,47(7):1179-1183.
    [9]
    Petersen I R, McFarlane D C. Robust state estimation for uncertain systems[C]//Proceedings of the 30th IEEE Conference on Decision and Control Part 1(of 3), December 11, 1991-December 13, 1991, Brighton, Engl, 1991:2630-2631.
    [10]
    Wang Zidong, Yang Fuwen, Ho D W C, et al. Robust finite-horizon filter for stochastic systems with missing measurements[J]. IEEE Signal Processing Letters, 2005,12(6):437-440.
    [11]
    Dong Hongli, Wang Zidong, Ho D W C, et al. Variance-constrained H ∞filter for a class of nonlinear time-varying systems with multiple missing measurements:the finite-horizon case[J]. IEEE Transactions on Signal Processing, 2010,58(5):2534-2543.
    [12]
    Xiong Junlin, Lam J. Fixed-order robust Hfilter design for Markovian jump systems with uncertain switching probabilities[J]. IEEE Transactions on Signal Processing, 2006,54(4):1421-1430.
    [13]
    Yaz E E, Hounkpevi F O. Robust minimum variance linear state estimators for multiple sensors with different failure rates[J]. Automatica, 2007,43(7):1274-1280.
    [14]
    Cao Chengtao, Xie Lihua, Zhang Huanshui, et al. A robust channel estimator for DS-CDMA systems under multipath fading channels[J]. IEEE Transactions on Signal Processing, 2006,54(1):13-22.
    [15]
    Lu Xiao, Wang Wei, Zhang Huanshui, et al. Robust Kalman filter for discrete-time systems with measurement delay[C]//Sixth World Congress on Intelligent Control and Automation, 21-23 June 2006, Piscataway, NJ, USA, 2006.
    [16]
    Wang Zidong, Ho D W C, Liu Xiaohui. Variance-constrained filter for uncertain stochastic systems with missing measurements[J]. IEEE Transactions on Automatic Control, 2003,48(7):1254-1258.
    [17]
    Wang Zidong, Huang Biao. Robust H 2/H ∞filter for linear systems with error variance constraints[J]. EEE Transactions on Signal Processing, 2000,48(8):2463-2467.
    [18]
    Nahi N E, Knobbe E J. Optimal linear recursive estimation with uncertain system parameters[J]. IEEE Transactions on Automatic Control, 1976,21(2):263-266.
    [19]
    Zhao Haiyan, Chen Hong. Moving horizon estimation for stochastic systems with missing measurements[J]. Journal of Jilin University (Engineering and Technology Edition), 2007,37(2):396-400.
    [20]
    Wei Guoliang, Wang Zidong, Shu Huisheng. Robust filter with stochastic nonlinearities and multiple missing measurements[J]. Automatica, 2009,45(3):836-841.
    [21]
    Zhang Hao, Chen Qijun, Yan Huaicheng, et al. Robust H ∞filter for switched stochastic system with missing measurements[J]. IEEE Transactions on Signal Processing, 2009,57(9):3466-3474.
    [22]
    Hu Jun, Wang Zidong, Gao Huijun, et al. Extended Kalman filter with stochastic nonlinearities and multiple missing measurements[J]. Automatica, 2012,48(9):2007-2015.
    [23]
    Mohamed S M K, Nahavandi S. Robust finite-horizon Kalman filter for uncertain discrete-time systems[J]. IEEE Transactions on Automatic Control, 2012,57(6):1548-1552.
    [24]
    Zeng Ming, Feng Jianxin, Yu Zhiwei. Optimal robust Kalman-type recursive filter for uncertain systems with finite-step autocorrelated process noises and missing measurements[C]//20112nd International Conference on Intelligent Control and Information Processing (ICICIP), 25-28 July 2011, Piscataway, NJ, USA, 2011.
    [25]
    Zhe Dong, Zheng You. Finite-horizon robust Kalman filter for uncertain discrete time-varying systems with uncertain-covariance white noises[J]. IEEE Signal Processing Letters, 2006,13(8):493-496.
    • Relative Articles
  • Supplements (0)
  • Cited By
  • 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
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (622) PDF downloads(533) Cited by()
    Proportional views
    Related

    Address:5 Zhongguancun South Street, Haidian District, Beijing

    Tel:86-10-68914374

    Email:blgywb@bit.edu.cn

    Copy Right © Journal of Beijing Institute of Technology

    Supported by:Beijing Renhe Information Technology Co. Ltd

    /

      Return
      Return
        Baidu
        map