• DocumentCode
    21002
  • Title

    Adaptive Fading Memory {{\\bf H}_\\infty } Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors

  • Author

    Tamboli, Prakash Kumar ; Duttagupta, Siddhartha P. ; Roy, Kallol

  • Author_Institution
    Electr. Eng., Indian Inst. of Technol. Bombay, Mumbai, India
  • Volume
    62
  • Issue
    4
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    1857
  • Lastpage
    1864
  • Abstract
    The paper deals with dynamic compensation of delayed Self Powered Flux Detectors (SPFDs) using discrete time H filtering method for improving the response of SPFDs with significant delayed components such as Platinum and Vanadium SPFD. We also present a comparative study between the Linear Matrix Inequality (LMI) based H filtering and Algebraic Riccati Equation (ARE) based Kalman filtering methods with respect to their delay compensation capabilities. Finally an improved recursive H filter based on the adaptive fading memory technique is proposed which provides an improved performance over existing methods. The existing delay compensation algorithms do not account for the rate of change in the signal for determining the filter gain and therefore add significant noise during the delay compensation process. The proposed adaptive fading memory H filter minimizes the overall noise very effectively at the same time keeps the response time at minimum values. The recursive algorithm is easy to implement in real time as compared to the LMI (or ARE) based solutions.
  • Keywords
    H filters; Riccati equations; adaptive filters; linear matrix inequalities; recursive estimation; recursive filters; Kalman filtering methods; Platinum; Vanadium; adaptive fading memory technique; algebraic Riccati equation; delay compensation algorithms; delayed components; delayed self powered flux detectors; discrete time filtering method; filter gain; linear matrix inequality; recursive filter; response time; Delays; Fading; Kalman filters; Mathematical model; Neutrons; Noise; Time factors; Adaptive filters; Kalman filters; minimax techniques; signal to noise ratio;
  • fLanguage
    English
  • Journal_Title
    Nuclear Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9499
  • Type

    jour

  • DOI
    10.1109/TNS.2015.2445829
  • Filename
    7163636