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A Novel Fuzzy-Affine-Model-Based Finite Frequency Filtering Design for 2-D Nonlinear Systems

Meng Wang, Jianbin Qiu, Huaicheng Yan

2024IEEE Transactions on Systems Man and Cybernetics Systems15 citationsDOI

Abstract

This work investigates the problem of piecewise affine (PWA) filtering design for two-dimensional (2-D) Roesser nonlinear systems with finite frequency performance based on Takagi–Sugeno (T–S) fuzzy affine models. The goal is to synthesize a 2-D PWA filter such that the resulting filtering error system is asymptotically stable and simultaneously satisfies a finite frequency <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathscr{H}_{\infty}$</tex-math> </inline-formula> performance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\gamma$</tex-math> </inline-formula> . With the utilization of the state space partition knowledge on 2-D fuzzy models, a novel PWA filter is obtained. By exploiting the 2-D Fourier transform technique to convert 2-D disturbances into their frequency domain counterparts, finite frequency <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathscr{H}_{\infty}$</tex-math> </inline-formula> performance analysis conditions are established, and then by applying projection lemma, an admissible frequency information-based filter design approach is proposed for 2-D Roesser nonlinear systems. Finally, the effectiveness of the PWA finite frequency filtering synthesis approach is validated through simulation studies on two examples.

Topics & Concepts

Nonlinear systemFilter (signal processing)MathematicsAffine transformationAlgorithmFrequency domainApplied mathematicsAlgebra over a fieldDiscrete mathematicsPure mathematicsComputer scienceMathematical analysisPhysicsComputer visionQuantum mechanicsFuzzy Logic and Control SystemsStability and Control of Uncertain SystemsAdaptive Control of Nonlinear Systems