Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems

This paper introduces a systematic and comprehensive method to design a constrained fuzzy model predictive control (MPC) cooperated with integral sliding mode control (ISMC) based on the Takagi-Sugeno (T-S) fuzzy model for uncertain continuous-time nonlinear systems subject to external disturbances....

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Mohsen Farbood, Mohammad Veysi, Mokhtar Shasadeghi, Afshin Izadian, Taher Niknam, Jamshid Aghaei
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	T-S fuzzy models (TSFMs) model predictive control (MPC) integral sliding mode control (ISMC) DC-DC buck converter flexible joint robot Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/db3761f7731c40d19cf6a6e85981082d
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:db3761f7731c40d19cf6a6e85981082d
record_format	dspace
spelling	oai:doaj.org-article:db3761f7731c40d19cf6a6e85981082d2021-11-18T00:08:06ZRobustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems2169-353610.1109/ACCESS.2021.3123513https://doaj.org/article/db3761f7731c40d19cf6a6e85981082d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9590515/https://doaj.org/toc/2169-3536This paper introduces a systematic and comprehensive method to design a constrained fuzzy model predictive control (MPC) cooperated with integral sliding mode control (ISMC) based on the Takagi-Sugeno (T-S) fuzzy model for uncertain continuous-time nonlinear systems subject to external disturbances. The proposed controller benefits from the robustness, optimality, and practical constraints considerations. The robustness against the uncertainties and matched external disturbances is achieved by the proposed ISMC without iterative calculation for obtaining the robust invariant set. The MPC schemes are designed separately based on the both quadratic and non-quadratic Lyapunov functions. By the proposed MPC, the states of the system reach the desired values in the optimal, constrained, and robust manner against the unmatched external disturbances. New linear matrix inequalities (LMIs) conditions are proposed to design both the proposed MPC schemes. Also, the practical constraints on the control signals are guaranteed in the design procedure based on the invariant ellipsoid set. To evaluate the effectiveness of the suggested strategy, some simulation and experimental tests were run.Mohsen FarboodMohammad VeysiMokhtar ShasadeghiAfshin IzadianTaher NiknamJamshid AghaeiIEEEarticleT-S fuzzy models (TSFMs)model predictive control (MPC)integral sliding mode control (ISMC)DC-DC buck converterflexible joint robotElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 147874-147887 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	T-S fuzzy models (TSFMs) model predictive control (MPC) integral sliding mode control (ISMC) DC-DC buck converter flexible joint robot Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	T-S fuzzy models (TSFMs) model predictive control (MPC) integral sliding mode control (ISMC) DC-DC buck converter flexible joint robot Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mohsen Farbood Mohammad Veysi Mokhtar Shasadeghi Afshin Izadian Taher Niknam Jamshid Aghaei Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
description	This paper introduces a systematic and comprehensive method to design a constrained fuzzy model predictive control (MPC) cooperated with integral sliding mode control (ISMC) based on the Takagi-Sugeno (T-S) fuzzy model for uncertain continuous-time nonlinear systems subject to external disturbances. The proposed controller benefits from the robustness, optimality, and practical constraints considerations. The robustness against the uncertainties and matched external disturbances is achieved by the proposed ISMC without iterative calculation for obtaining the robust invariant set. The MPC schemes are designed separately based on the both quadratic and non-quadratic Lyapunov functions. By the proposed MPC, the states of the system reach the desired values in the optimal, constrained, and robust manner against the unmatched external disturbances. New linear matrix inequalities (LMIs) conditions are proposed to design both the proposed MPC schemes. Also, the practical constraints on the control signals are guaranteed in the design procedure based on the invariant ellipsoid set. To evaluate the effectiveness of the suggested strategy, some simulation and experimental tests were run.
format	article
author	Mohsen Farbood Mohammad Veysi Mokhtar Shasadeghi Afshin Izadian Taher Niknam Jamshid Aghaei
author_facet	Mohsen Farbood Mohammad Veysi Mokhtar Shasadeghi Afshin Izadian Taher Niknam Jamshid Aghaei
author_sort	Mohsen Farbood
title	Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
title_short	Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
title_full	Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
title_fullStr	Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
title_full_unstemmed	Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems
title_sort	robustness improvement of computationally efficient cooperative fuzzy model predictive-integral sliding mode control of nonlinear systems
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/db3761f7731c40d19cf6a6e85981082d
work_keys_str_mv	AT mohsenfarbood robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems AT mohammadveysi robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems AT mokhtarshasadeghi robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems AT afshinizadian robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems AT taherniknam robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems AT jamshidaghaei robustnessimprovementofcomputationallyefficientcooperativefuzzymodelpredictiveintegralslidingmodecontrolofnonlinearsystems
_version_	1718425253983551488

Robustness Improvement of Computationally Efficient Cooperative Fuzzy Model Predictive-Integral Sliding Mode Control of Nonlinear Systems

Ejemplares similares