Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables

This paper proposes an <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> reset unknown input observer (R-UIO) based on the Takagi-Sugeno (T-S) fuzzy model for the state estimation of nonlinear uncertain systems. Firstly, <inli...

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Autores principales:	Zeinab Echreshavi, Mokhtar Shasadeghi, Mohammad Hasan Asemani, Saleh Mobayen, Afef Fekih
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	T-S fuzzy system reset mechanism unknown inputs (UIs) unmeasurable premise variables external disturbance Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/4211727a19e84605a45bc426488ad6df
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spelling	oai:doaj.org-article:4211727a19e84605a45bc426488ad6df2021-11-17T00:00:56ZFuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables2169-353610.1109/ACCESS.2021.3125952https://doaj.org/article/4211727a19e84605a45bc426488ad6df2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9605253/https://doaj.org/toc/2169-3536This paper proposes an <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> reset unknown input observer (R-UIO) based on the Takagi-Sugeno (T-S) fuzzy model for the state estimation of nonlinear uncertain systems. Firstly, <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> unknown input observer (UIO) is designed for TSFM-based nonlinear systems with measurable and unmeasurable premise variables. Then, according to the importance of observers based on unmeasurable premise variables, the results on UIO is modified to propose R-UIO. The sufficient conditions for the stabilization of the estimation error are derived in terms of linear matrix inequalities (LMIs). The proposed R-UIO benefits from less computation complexity to find the feasible parameters, improvement of the estimation process in viewpoints of convergence speed and overshoot. To verify the effectiveness of the recommended approaches, the methods are applied to a practical system.Zeinab EchreshaviMokhtar ShasadeghiMohammad Hasan AsemaniSaleh MobayenAfef FekihIEEEarticleT-S fuzzy systemreset mechanismunknown inputs (UIs)unmeasurable premise variablesexternal disturbanceElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 151729-151740 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	T-S fuzzy system reset mechanism unknown inputs (UIs) unmeasurable premise variables external disturbance Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	T-S fuzzy system reset mechanism unknown inputs (UIs) unmeasurable premise variables external disturbance Electrical engineering. Electronics. Nuclear engineering TK1-9971 Zeinab Echreshavi Mokhtar Shasadeghi Mohammad Hasan Asemani Saleh Mobayen Afef Fekih Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
description	This paper proposes an <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> reset unknown input observer (R-UIO) based on the Takagi-Sugeno (T-S) fuzzy model for the state estimation of nonlinear uncertain systems. Firstly, <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> unknown input observer (UIO) is designed for TSFM-based nonlinear systems with measurable and unmeasurable premise variables. Then, according to the importance of observers based on unmeasurable premise variables, the results on UIO is modified to propose R-UIO. The sufficient conditions for the stabilization of the estimation error are derived in terms of linear matrix inequalities (LMIs). The proposed R-UIO benefits from less computation complexity to find the feasible parameters, improvement of the estimation process in viewpoints of convergence speed and overshoot. To verify the effectiveness of the recommended approaches, the methods are applied to a practical system.
format	article
author	Zeinab Echreshavi Mokhtar Shasadeghi Mohammad Hasan Asemani Saleh Mobayen Afef Fekih
author_facet	Zeinab Echreshavi Mokhtar Shasadeghi Mohammad Hasan Asemani Saleh Mobayen Afef Fekih
author_sort	Zeinab Echreshavi
title	Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
title_short	Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
title_full	Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
title_fullStr	Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
title_full_unstemmed	Fuzzy Reset-Based <italic>H</italic><sub>∞</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
title_sort	fuzzy reset-based <italic>h</italic><sub>∞</sub> unknown input observer design for uncertain nonlinear systems with unmeasurable premise variables
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/4211727a19e84605a45bc426488ad6df
work_keys_str_mv	AT zeinabechreshavi fuzzyresetbaseditalichitalicsubx221esubunknowninputobserverdesignforuncertainnonlinearsystemswithunmeasurablepremisevariables AT mokhtarshasadeghi fuzzyresetbaseditalichitalicsubx221esubunknowninputobserverdesignforuncertainnonlinearsystemswithunmeasurablepremisevariables AT mohammadhasanasemani fuzzyresetbaseditalichitalicsubx221esubunknowninputobserverdesignforuncertainnonlinearsystemswithunmeasurablepremisevariables AT salehmobayen fuzzyresetbaseditalichitalicsubx221esubunknowninputobserverdesignforuncertainnonlinearsystemswithunmeasurablepremisevariables AT afeffekih fuzzyresetbaseditalichitalicsubx221esubunknowninputobserverdesignforuncertainnonlinearsystemswithunmeasurablepremisevariables
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Fuzzy Reset-Based <italic>H</italic><sub>&#x221E;</sub> Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables

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