A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 3 Issue 1
Jan.  2016

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 6.171, Top 11% (SCI Q1)
    CiteScore: 11.2, Top 5% (Q1)
    Google Scholar h5-index: 51, TOP 8
Turn off MathJax
Article Contents
Dong Shen and Yun Xu, "Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 1, pp. 59-67, 2016.
Citation: Dong Shen and Yun Xu, "Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 1, pp. 59-67, 2016.

Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information

Funds:

This work was supported by National Natural Science Foundation of China (61304085) and Beijing Natural Science Foundation (4152040).

  • An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to guarantee an adaptive improvement in tracking performance. A decreasing learning gain is introduced into the algorithm to suppress the effects of stochastic noises and quantization errors. The input sequence is proved to converge strictly to the optimal input under the given index. Illustrative simulations are given to verify the theoretical analysis.

     

  • loading
  • [1]
    Arimoto S, Kawamura S, Miyazaki F. Bettering operation of robots by learning. Journal of Robotic Systems, 1984, 1(2):123-140
    [2]
    Bristow D A, Tharayil M, Alleyne A G. A survey of iterative learning control:a learning-based method for high-performance tracking control. IEEE Control Systems Magazine, 2006, 26(3):96-114
    [3]
    Ahn H S, Chen Y Q, Moore K L. Iterative learning control:brief survey and categorization. IEEE Transactions on Systems, Man, and Cybernetics, Part C:Applications and Reviews, 2007, 37(6):1099-1121
    [4]
    Shen D, Wang Y Q. Survey on stochastic iterative learning control. Journal of Process Control, 2014, 24(12):64-77
    [5]
    Curry R E. Estimation and Control with Quantized Measurements. Cambridge:MIT Press, 1970.
    [6]
    Wang L Y, Yin G G, Zhang J F, Zhao Y L. System Identification with Quantized Observations. Boston:Birkhäuser, 2010.
    [7]
    Jiang Z P, Liu T F. Quantized nonlinear control-a survey. Acta Automatica Sinica, 2013, 39(11):1820-1830
    [8]
    Brockett R W, Liberzon D. Quantized feedback stabilization of linear systems. IEEE Transactions on Automatic Control, 2000, 45(7):1279-1289
    [9]
    Fagnani F, Zampieri S. Quantized stabilization of linear systems:complexity versus performance. IEEE Transactions on Automatic Control, 2004, 49(9):1534-1548
    [10]
    Bu X H, Wang T H, Hou Z S, Chi R H. Iterative learning control for discrete-time systems with quantised measurements. IET Control Theory & Applications, 2015, 9(9):1455-1460
    [11]
    Elia N, Mitter S K. Stabilization of linear systems with limited information. IEEE Transactions on Automatic Control, 2001, 46(9):1384-1400
    [12]
    Fu M Y, Xie L H. The sector bound approach to quantized feedback control. IEEE Transactions on Automatic Control, 2005, 50(11):1698-1710
    [13]
    Chen H F. Stochastic Approximation and its Applications. Dordrecht, the Netherlands:Kluwer Academic Publishers, 2002.

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

    Article Metrics

    Article views (1226) PDF downloads(11) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return