New hybrid model for nonlinear systems via Takagi-Sugeno fuzzy approach

Mathematical models, especially complex nonlinear systems, are always difficult to analyze and synthesize, and researchers need effective and suitable control methods to address these issues. In the present work, we proposed a hybrid method that combines the well-known Takagi-Sugeno fuzzy model with...

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Bibliographic Details
Published inAIMS mathematics Vol. 9; no. 9; pp. 23197 - 23220
Main Authors Ben Mabrouk, Anouar, Alanazi, Abdulaziz, Bassfar, Zaid, Alanazi, Dalal
Format Journal Article
LanguageEnglish
Published AIMS Press 01.01.2024
Subjects
control
dynamical systems
fuzzy model
lyapunov stability
nonlinear systems
wavelets
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Summary:Mathematical models, especially complex nonlinear systems, are always difficult to analyze and synthesize, and researchers need effective and suitable control methods to address these issues. In the present work, we proposed a hybrid method that combines the well-known Takagi-Sugeno fuzzy model with wavelet decomposition to investigate nonlinear systems characterized by the presence of mixed nonlinearities. Here, one nonlinearity is super-linear and convex, and other is sub-linear, concave, and singular at zero, which leads to difficulties in the analysis, as is known in PDE theory. Linear and polynomial fuzzy models were combined with wavelets to ensure an improvement in both methods for investigating such problems. The results showed a high performance compared with existing methods via error estimates and Lyapunov theory of stability. The model was applied to a prototype nonlinear Schrödinger dynamical system.
ISSN:2473-6988
2473-6988
DOI:10.3934/math.20241128