• DocumentCode
    2577877
  • Title

    Optimal quantization interval design of dynamic quantizers which satisfy the communication rate constraints

  • Author

    Okajima, Hiroshi ; Matsunaga, Nobutomo ; Sawada, Kenji

  • Author_Institution
    Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    4733
  • Lastpage
    4739
  • Abstract
    This paper proposes the design method of the dynamic quantizer for the networked control systems. It is well known that the dynamic quantizers, which consist of filter and static quantizer, are effective for compressing the data with small quantization error of control. Many methods for designing the dynamic quantizers have been proposed from the perspective of filter design. When it is required to control with network communication, the data size of signal should be minified appropriately by quantizers because of the communication rate constraint. Since the quantization interval (distance between two quantizer outputs) of the quantizer makes an impact on the data rate, determination of quantization interval is important matter in the dynamic quantizers. However, the design method of quantization interval has not been proposed explicitly in the past researches of the dynamic quantizer design. In this paper, we propose the design method of the smaller quantization interval which satisfy the communication rate constraints. The design method is derived as an LMI problem based on the invariant set analysis. By the proposed method, the quantization interval guarantees that the signals are quantized appropriately within the given data size. The effectiveness is illustrated by numerical examples.
  • Keywords
    control system synthesis; distributed control; linear matrix inequalities; optimal control; LMI problem; communication rate constraints; dynamic quantizers; filter design; networked control systems; optimal quantization interval design; quantization error; Control systems; Design methodology; Ellipsoids; Equations; Feedforward neural networks; Optimized production technology; Quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2010 49th IEEE Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4244-7745-6
  • Type

    conf

  • DOI
    10.1109/CDC.2010.5717778
  • Filename
    5717778