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

Niko Moustakis; Shuai Yuan; Simone Baldi

doi:10.23919/ECC.2018.8550109

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 volume › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

88 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings of 2018 European Control Conference (ECC2018)
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	2423-2428
ISBN (Electronic)	978-3-9524-2698-2
ISBN (Print)	978-3-9524-2699-9
DOIs	https://doi.org/10.23919/ECC.2018.8550109
Publication status	Published - 2018
Event	16th European Control Conference, ECC 2018 - Limassol, Cyprus Duration: 12 Jun 2018 → 15 Jun 2018 http://www.ecc18.eu/

Conference

Conference	16th European Control Conference, ECC 2018
Abbreviated title	ECC 2018
Country/Territory	Cyprus
City	Limassol
Period	12/06/18 → 15/06/18
Internet address	http://www.ecc18.eu/

Bibliographical note

Accepted Author Manuscript

Keywords

asymptotic tracking
Hybrid dynamic quantization
input quantization
model reference adaptive control

Access to Document

10.23919/ECC.2018.8550109

paper ECC 2018Accepted author manuscript, 253 KB

Cite this

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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",

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year = "2018",

doi = "10.23919/ECC.2018.8550109",

language = "English",

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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/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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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

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M3 - Conference contribution

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SP - 2423

EP - 2428

BT - Proceedings of 2018 European Control Conference (ECC2018)

PB - IEEE

CY - Piscataway, NJ, USA

T2 - 16th European Control Conference, ECC 2018

Y2 - 12 June 2018 through 15 June 2018

ER -

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

Abstract

Conference

Bibliographical note

Keywords

Access to Document

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