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Parameter estimate and adaptive control of DARMA systems with uniform quantized output data
  • Lida Jing
Lida Jing
Shandong University School of Mathematics

Corresponding Author:[email protected]

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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.
30 Sep 2023Submitted to International Journal of Robust and Nonlinear Control
03 Oct 2023Assigned to Editor
03 Oct 2023Submission Checks Completed
03 Oct 2023Review(s) Completed, Editorial Evaluation Pending
22 Oct 2023Reviewer(s) Assigned