• DocumentCode
    2649212
  • Title

    ANFIS parallel hybrid modeling method for optical encoder calibration

  • Author

    Wang Yanyong ; Deng Fang ; Sun Jian ; Xu Lishuan

  • Author_Institution
    Sch. of Autom., Beijing Inst. of Technol., Beijing, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    1591
  • Lastpage
    1596
  • Abstract
    A novel hybrid modeling method, combining the knowledge-based model and adaptive-network-based fuzzy inference system (ANFIS) model, is proposed in this paper. The modeling process is presented step by step. Firstly, a simulation based on a single-input nonlinear function is carried out to verify its feasibility and effectiveness, in comparison with results in the previous publication. Secondly, a calibration experiment based on a 16-bit absolute type encoder is presented. Significant improvements regarding the measurement accuracy of the encoder are achieved by employing the proposed approach with respect to original data and traditional algorithms.
  • Keywords
    angular measurement; calibration; computerised instrumentation; fuzzy reasoning; knowledge based systems; optical sensors; 16-bit absolute type encoder; ANFIS model; adaptive network-based fuzzy inference system; knowledge based model; measurement accuracy; optical encoder calibration; parallel hybrid modeling method; single-input nonlinear function; word length 16 bit; Accuracy; Adaptation models; Calibration; Knowledge based systems; Measurement uncertainty; Polynomials; Rotation measurement; ANFIS; Calibration; Encoder; Knowledge-based model; Repeatability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2012 24th Chinese
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4577-2073-4
  • Type

    conf

  • DOI
    10.1109/CCDC.2012.6243010
  • Filename
    6243010