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Recursive Least-Squares Estimation for Hammerstein Nonlinear Systems with Nonuniform Sampling

Author

Listed:
  • Xiangli Li
  • Lincheng Zhou
  • Ruifeng Ding
  • Jie Sheng

Abstract

This paper focuses on the identification problem of Hammerstein nonlinear systems with nonuniform sampling. Using the key-term separation principle, we present a discrete identification model with nonuniform sampling input and output data based on the frame period. To estimate parameters of the presented model, an auxiliary model-based recursive least-squares algorithm is derived by replacing the unmeasurable variables in the information vector with their corresponding recursive estimates. The simulation results show the effectiveness of the proposed algorithm.

Suggested Citation

  • Xiangli Li & Lincheng Zhou & Ruifeng Ding & Jie Sheng, 2013. "Recursive Least-Squares Estimation for Hammerstein Nonlinear Systems with Nonuniform Sampling," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-8, November.
    • Handle: RePEc:hin:jnlmpe:240929
    DOI: 10.1155/2013/240929
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