Stable fuzzy controllers via LMI approach for non-linear systems described by type-2 T–S fuzzy model
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 28 June 2021
Issue publication date: 15 July 2021
Abstract
Purpose
The purpose of this paper is to stabilize the type-2 Takagi–Sugeno (T–S) fuzzy systems with the sufficient and guaranteed stability conditions. The given conditions efficaciously handle parameter uncertainties by the upper and lower membership functions of the type-2 fuzzy sets (FSs).
Design/methodology/approach
This paper reports on a relevant study of stable fuzzy controllers and type-2 T–S fuzzy systems and reported that the synthesis of controller for nonlinear systems described by the type-2 T–S fuzzy model is a key problem and it can be resolve to convex problems via linear matrix inequalities (LMIs).
Findings
The multigain fuzzy controllers are established to improve the solvability of the stability conditions, and the authors design multigain fuzzy controllers which have extensive information of upper and lower membership grades. Consequently, the authors derive the traditional stability condition in terms of LMIs. One simulation examples illustrate the effectiveness and robustness of the derived stabilization conditions.
Originality/value
The uncertain MIMO nonlinear system described by Type-2 Takagi-Sugeno (T-S) fuzzy model, and successively LMI approach used to determine the system stability conditions. The proposed control approach will give superior fault-tolerant control permanence under the actuator fault [partial loss of effectiveness (LOE)]. Also the controller robust against the unmeasurable process disturbances. Additionally, the statistical z-test are carried out to validate the proposed control approach against the control approach proposed by Himanshukumar and Vipul (2019a).
Keywords
Acknowledgements
The project outcome is Ph.D work of corresponding author of this article. This research received no external funding. The authors would also like to thank Department of Instrumentation and Control, Faculty of Technology, Dharmsinh Desai University, Nadiad 387001, Gujarat, India.Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.Author contributions: Conceptualization, H.R.P.; methodology, H.R.P.; software, H.R.P.; validation, H.R.P.; formal analysis, H.R.P.; investigation, H.R.P.; resources, H.R.P. and V.A.S.; data curation, H.R.P.; writing—original draft preparation, H.R.P.; writing—review and editing, H.R.P. and V.A.S.; supervision, V.A.S.; All authors have read and agreed to the published version of the manuscript.Conflict of interest: The authors declare that they have no conflict of interest.
Citation
Patel, H.R. and Shah, V.A. (2021), "Stable fuzzy controllers via LMI approach for non-linear systems described by type-2 T–S fuzzy model", International Journal of Intelligent Computing and Cybernetics, Vol. 14 No. 3, pp. 509-531. https://doi.org/10.1108/IJICC-02-2021-0024
Publisher
:Emerald Publishing Limited
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