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Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers

This paper focuses on robustness and sensitivity analysis for sensor fault diagnosis of a voltage source converter based microgrid model. It uses robust control parameters such as minimum sensitivity parameter [Formula: see text] , maximum robustness parameter [Formula: see text] , and compromised b...

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Autores principales: Shahzad, Ebrahim, Khan, Adnan Umar, Iqbal, Muhammad, Albalawi, Fahad, Khan, Muhammad Attique, Saeed, Ahmad, Ghoneim, Sherif S. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879389/
https://www.ncbi.nlm.nih.gov/pubmed/35214494
http://dx.doi.org/10.3390/s22041597
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author Shahzad, Ebrahim
Khan, Adnan Umar
Iqbal, Muhammad
Albalawi, Fahad
Khan, Muhammad Attique
Saeed, Ahmad
Ghoneim, Sherif S. M.
author_facet Shahzad, Ebrahim
Khan, Adnan Umar
Iqbal, Muhammad
Albalawi, Fahad
Khan, Muhammad Attique
Saeed, Ahmad
Ghoneim, Sherif S. M.
author_sort Shahzad, Ebrahim
collection PubMed
description This paper focuses on robustness and sensitivity analysis for sensor fault diagnosis of a voltage source converter based microgrid model. It uses robust control parameters such as minimum sensitivity parameter [Formula: see text] , maximum robustness parameter [Formula: see text] , and compromised both [Formula: see text] , being incorporated in the sliding mode observer theory using the game theoretic saddle point estimation achieved through convex optimization of constrained LMIs. The approach used works in a way that the mentioned robust control parameters are embedded in Hamilton–Jacobi–Isaacs-Equation (HJIE) and are also used to determine the inequality version of HJIE, which is, in terms of the Lyapunov function, faults/disturbances and augmented state/output estimation error as its variables. The stability analysis is also presented by negative definiteness of the same inequality version of HJIE, and additionally, it also gives linear matrix inequalities (LMIs), which are optimized using iterative convex optimization algorithms to give optimal sliding mode observer gains enhanced with robustness to maximal preset values of disturbances and sensitivity to minimal preset values of faults. The enhanced sliding mode observer is used to estimate states, faults, and disturbances using sliding mode observer theory. The optimality of sliding mode observer gains for sensitivity of the observer to minimal faults and robustness to maximal disturbance is a game theoretic saddle point estimation achieved through convex optimization of LMIs. The paper includes results for state estimation errors, faults’ estimation/reconstruction, fault estimation errors, and fault-tolerant-control performance for current and potential transformer faults. The considered faults and disturbances in current and potential transformers are sinusoidal nature composite of magnitude/phase/harmonics at the same time.
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spelling pubmed-88793892022-02-26 Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers Shahzad, Ebrahim Khan, Adnan Umar Iqbal, Muhammad Albalawi, Fahad Khan, Muhammad Attique Saeed, Ahmad Ghoneim, Sherif S. M. Sensors (Basel) Article This paper focuses on robustness and sensitivity analysis for sensor fault diagnosis of a voltage source converter based microgrid model. It uses robust control parameters such as minimum sensitivity parameter [Formula: see text] , maximum robustness parameter [Formula: see text] , and compromised both [Formula: see text] , being incorporated in the sliding mode observer theory using the game theoretic saddle point estimation achieved through convex optimization of constrained LMIs. The approach used works in a way that the mentioned robust control parameters are embedded in Hamilton–Jacobi–Isaacs-Equation (HJIE) and are also used to determine the inequality version of HJIE, which is, in terms of the Lyapunov function, faults/disturbances and augmented state/output estimation error as its variables. The stability analysis is also presented by negative definiteness of the same inequality version of HJIE, and additionally, it also gives linear matrix inequalities (LMIs), which are optimized using iterative convex optimization algorithms to give optimal sliding mode observer gains enhanced with robustness to maximal preset values of disturbances and sensitivity to minimal preset values of faults. The enhanced sliding mode observer is used to estimate states, faults, and disturbances using sliding mode observer theory. The optimality of sliding mode observer gains for sensitivity of the observer to minimal faults and robustness to maximal disturbance is a game theoretic saddle point estimation achieved through convex optimization of LMIs. The paper includes results for state estimation errors, faults’ estimation/reconstruction, fault estimation errors, and fault-tolerant-control performance for current and potential transformer faults. The considered faults and disturbances in current and potential transformers are sinusoidal nature composite of magnitude/phase/harmonics at the same time. MDPI 2022-02-18 /pmc/articles/PMC8879389/ /pubmed/35214494 http://dx.doi.org/10.3390/s22041597 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shahzad, Ebrahim
Khan, Adnan Umar
Iqbal, Muhammad
Albalawi, Fahad
Khan, Muhammad Attique
Saeed, Ahmad
Ghoneim, Sherif S. M.
Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title_full Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title_fullStr Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title_full_unstemmed Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title_short Fault Diagnostics and Tolerance Analysis of a Microgrid System Using Hamilton–Jacobi–Isaacs Equation and Game Theoretic Estimations in Sliding Mode Observers
title_sort fault diagnostics and tolerance analysis of a microgrid system using hamilton–jacobi–isaacs equation and game theoretic estimations in sliding mode observers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879389/
https://www.ncbi.nlm.nih.gov/pubmed/35214494
http://dx.doi.org/10.3390/s22041597
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