Quantized identification of ARMA systems with colored measurement noise

• Chengpu Yu ^[1] ; Keyou You ^[2] ; Lihua Xie ^[3]
  1. [1] Delft University of Technology

     Delft University of Technology

     Países Bajos

     
  2. [2] Tsinghua University

     Tsinghua University

     China

     
  3. [3] Nanyang Technological University

     Nanyang Technological University

     Singapur

     

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• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Vol. 66, 2016, págs. 101-108
• Idioma: inglés
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• Resumen

  • This paper studies the identification of ARMA systems with colored measurement noises using finite-level quantized observations. Compared with the case under colorless noises, this problem is more challenging. Our approach is to jointly design an adaptive quantizer and a recursive estimator to identify system parameters. Specifically, the quantizer uses the latest estimate to adjust its thresholds, and the estimator is updated by using quantized observations. To accommodate the temporal correlations of quantization errors and measurement noises, we construct a second-order statistics equivalent system, from which the original ARMA system is identified. The associated identifiability problem and convergence are analyzed as well. Finally, numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm.