An adaptive approach to zooming-based control for uncertain systems with input quantization

Niko Moustakis, Shuai Yuan, Simone Baldi

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)
25 Downloads (Pure)


This paper establishes an adaptive tracking approach for linear systems with parametric uncertainties, when input measurements are quantized due to the presence of a communication network closing the control loop. In order to address the tracking problem, a novel dynamic quantizer with dynamic offset is introduced and embedded into an adaptive hybrid control strategy based on zooming mechanism. A Lyapunov-based approach is used to derive the adaptive adjustments for the control gains and for the dynamic range and dynamic offset of the quantizer: it is proven analytically that the proposed adjustments guarantee asymptotic state tracking. Quantized adaptive control of an electrohydraulic system is given as an example of the effectiveness of the designed control methodology.

Original languageEnglish
Title of host publicationProceedings of 2018 European Control Conference (ECC2018)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-3-9524-2698-2
ISBN (Print)978-3-9524-2699-9
Publication statusPublished - 2018
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus
Duration: 12 Jun 201815 Jun 2018


Conference16th European Control Conference, ECC 2018
Abbreviated titleECC 2018
Internet address


  • asymptotic tracking
  • Hybrid dynamic quantization
  • input quantization
  • model reference adaptive control

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