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\begin{document}

\title{Parameter estimate and adaptive control of DARMA systems with uniform
quantized output data}



\author[1]{Lida Jing}%
\affil[1]{Shandong University School of Mathematics}%


\vspace{-1em}



  
  \date{May 24, 2024}


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\begin{abstract}
This paper is concerned with parameter estimate and adaptive control
problems of deterministic autoregressive moving average (DARMA) systems
on the basis of quantized data of system output signals which are
generated by a kind of uniform quantizer. By designing system input
signals, the extended least-squares (ELS) algorithm with uniform output
observations is proved to yield bounded estimation errors under some
mild assumptions. Moreover, the adaptive tracking controller under
inaccuracy observations are also designed. To analyse the properties of
tracking error, I use the expanded form of ELS and research the
properties of quantization noise. In addition, I give the expression of
tracking error and show how it depends on the size of quantization step
when the quantization step satisfies some conditions. A numerical
example is supplied to demonstrate the theoretical results.%
\end{abstract}%



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