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An adaptive approach to zooming-based control for uncertain systems with input quantization. / Moustakis, Niko; Yuan, Shuai; Baldi, Simone.

Proceedings of 2018 European Control Conference (ECC2018). Piscataway, NJ, USA : IEEE, 2018. p. 2423-2428 8550109.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Moustakis, N, Yuan, S & Baldi, S 2018, An adaptive approach to zooming-based control for uncertain systems with input quantization. in Proceedings of 2018 European Control Conference (ECC2018)., 8550109, IEEE, Piscataway, NJ, USA, pp. 2423-2428, 16th European Control Conference, ECC 2018, Limassol, Cyprus, 12/06/18. https://doi.org/10.23919/ECC.2018.8550109

APA

Moustakis, N., Yuan, S., & Baldi, S. (2018). An adaptive approach to zooming-based control for uncertain systems with input quantization. In Proceedings of 2018 European Control Conference (ECC2018) (pp. 2423-2428). [8550109] Piscataway, NJ, USA: IEEE. https://doi.org/10.23919/ECC.2018.8550109

Vancouver

Moustakis N, Yuan S, Baldi S. An adaptive approach to zooming-based control for uncertain systems with input quantization. In Proceedings of 2018 European Control Conference (ECC2018). Piscataway, NJ, USA: IEEE. 2018. p. 2423-2428. 8550109 https://doi.org/10.23919/ECC.2018.8550109

Author

Moustakis, Niko ; Yuan, Shuai ; Baldi, Simone. / An adaptive approach to zooming-based control for uncertain systems with input quantization. Proceedings of 2018 European Control Conference (ECC2018). Piscataway, NJ, USA : IEEE, 2018. pp. 2423-2428

BibTeX

@inproceedings{af70589564894e02b2f2db16217d0bad,
title = "An adaptive approach to zooming-based control for uncertain systems with input quantization",
abstract = "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.",
keywords = "asymptotic tracking, Hybrid dynamic quantization, input quantization, model reference adaptive control",
author = "Niko Moustakis and Shuai Yuan and Simone Baldi",
note = "Accepted Author Manuscript",
year = "2018",
doi = "10.23919/ECC.2018.8550109",
language = "English",
isbn = "978-3-9524-2699-9",
pages = "2423--2428",
booktitle = "Proceedings of 2018 European Control Conference (ECC2018)",
publisher = "IEEE",
address = "United States",

}

RIS

TY - GEN

T1 - An adaptive approach to zooming-based control for uncertain systems with input quantization

AU - Moustakis, Niko

AU - Yuan, Shuai

AU - Baldi, Simone

N1 - Accepted Author Manuscript

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - asymptotic tracking

KW - Hybrid dynamic quantization

KW - input quantization

KW - model reference adaptive control

UR - http://www.scopus.com/inward/record.url?scp=85059803906&partnerID=8YFLogxK

U2 - 10.23919/ECC.2018.8550109

DO - 10.23919/ECC.2018.8550109

M3 - Conference contribution

SN - 978-3-9524-2699-9

SP - 2423

EP - 2428

BT - Proceedings of 2018 European Control Conference (ECC2018)

PB - IEEE

CY - Piscataway, NJ, USA

ER -

ID: 50565399