Global sampled-data output-feedback stabilization for nonlinear systems with unknown measurement sensitivity

Pan Wang; Lin Chai; Chih Chiang Chen; Shumin Fei

doi:10.1002/rnc.4668

Global sampled-data output-feedback stabilization for nonlinear systems with unknown measurement sensitivity

Pan Wang, Lin Chai, Chih Chiang Chen, Shumin Fei

Department of Systems and Naval Mechatronic Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

This paper investigates the problem of global output-feedback stabilization by sampled-data control for nonlinear systems with unknown measurement sensitivity. By employing the technique of output-feedback domination, a sampled-data output-feedback control law together with a sampled-data state observer is explicitly constructed. By an exquisite selection of both the domination gain and sampling period, the resultant control law is a globally asymptotic stabilizer even in the presence of unknown measurement sensitivity. The novelty of this paper is the development of a distinct approach which can tackle the problem of output-feedback stabilization for the nonlinear systems with unknown measurement sensitivity.

Original language	English
Pages (from-to)	4909-4927
Number of pages	19
Journal	International Journal of Robust and Nonlinear Control
Volume	29
Issue number	14
DOIs	https://doi.org/10.1002/rnc.4668
Publication status	Published - 2019

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Chemical Engineering(all)
Biomedical Engineering
Aerospace Engineering
Mechanical Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

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title = "Global sampled-data output-feedback stabilization for nonlinear systems with unknown measurement sensitivity",

abstract = "This paper investigates the problem of global output-feedback stabilization by sampled-data control for nonlinear systems with unknown measurement sensitivity. By employing the technique of output-feedback domination, a sampled-data output-feedback control law together with a sampled-data state observer is explicitly constructed. By an exquisite selection of both the domination gain and sampling period, the resultant control law is a globally asymptotic stabilizer even in the presence of unknown measurement sensitivity. The novelty of this paper is the development of a distinct approach which can tackle the problem of output-feedback stabilization for the nonlinear systems with unknown measurement sensitivity.",

author = "Pan Wang and Lin Chai and Chen, {Chih Chiang} and Shumin Fei",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grants 61374038, 61374050, and 61473079, Top six talents in Jiangsu (No. RJFW-001), and the Ministry of Science and Technology (MOST), Taiwan, under Grant MOST 107-2221-E-006-231-.",

year = "2019",

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volume = "29",

pages = "4909--4927",

journal = "International Journal of Robust and Nonlinear Control",

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T1 - Global sampled-data output-feedback stabilization for nonlinear systems with unknown measurement sensitivity

AU - Wang, Pan

AU - Chai, Lin

AU - Chen, Chih Chiang

AU - Fei, Shumin

N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grants 61374038, 61374050, and 61473079, Top six talents in Jiangsu (No. RJFW-001), and the Ministry of Science and Technology (MOST), Taiwan, under Grant MOST 107-2221-E-006-231-.

PY - 2019

Y1 - 2019

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AB - This paper investigates the problem of global output-feedback stabilization by sampled-data control for nonlinear systems with unknown measurement sensitivity. By employing the technique of output-feedback domination, a sampled-data output-feedback control law together with a sampled-data state observer is explicitly constructed. By an exquisite selection of both the domination gain and sampling period, the resultant control law is a globally asymptotic stabilizer even in the presence of unknown measurement sensitivity. The novelty of this paper is the development of a distinct approach which can tackle the problem of output-feedback stabilization for the nonlinear systems with unknown measurement sensitivity.

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