A modified stochastic gradient based parameter estimation algorithm for dual-rate sampled-data systems

  • Authors:

  • Jie Ding;Yang Shi;Huigang Wang;Feng Ding

  • Affiliations:

  • School of Communication and Control Engineering, Jiangnan University, Wuxi 214122, China;Department of Mechanical Engineering, University of Victoria, PO Box 3055, STN CSC, Victoria, BC, Canada V8N 3P6;College of Marine Engineering, Northwestern Polytechnical University, Xi'an 710072, China;School of Communication and Control Engineering, Jiangnan University, Wuxi 214122, China

  • Venue:
  • Digital Signal Processing
  • Year:
  • 2010

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Abstract

In this paper, we propose a novel identification algorithm for a class of dual-rate sampled-data systems whose input-output data are measured by two different sampling rates. A polynomial transformation technique is employed to derive a mathematical model for such dual-rate systems. The proposed modified stochastic gradient algorithm has faster convergence rate than stochastic gradient algorithms for parameter identification using the dual-rate input-output data. Convergence properties of the algorithm are analyzed. Finally, illustrative and comparison examples are provided to verify the effectiveness and performance improvement of the proposed method.