T-S fuzzy control for MPPT of photovoltaic pumping system

Allouche, Moez; Dahech, Karim; Chaabane, Mohamed; Mehdi, Driss

doi:10.3233/jifs-17400

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…Currently, the knowledgeable T-S fuzzy models are viewed as a helpful manner for approaching nonlinear behaviors. 23,24 As a matter of fact, they represent the behavior of the nonlinear system by combining a set of local models with the weighting functions. This method is based on solving the linear matrix inequalities (LMIs), which gives us an excellent stability during the controller design.…”

Section: Introductionmentioning

confidence: 99%

“…The T-S approach has been investigated in the control of the WCS as in previous works. 24,25 These papers have highlighted the advantage of the LMI, which still needs the operational states of the WCS at MPP.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, the knowledgeable T‐S fuzzy models are viewed as a helpful manner for approaching nonlinear behaviors 23,24 . As a matter of fact, they represent the behavior of the nonlinear system by combining a set of local models with the weighting functions.…”

Section: Introductionmentioning

confidence: 99%

“…This method is based on solving the linear matrix inequalities (LMIs), which gives us an excellent stability during the controller design. The T‐S approach has been investigated in the control of the WCS as in previous works 24,25 . These papers have highlighted the advantage of the LMI, which still needs the operational states of the WCS at MPP.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent power control of wind conversion system based on Takagi–Sugeno fuzzy model

Abderrahim

Allouche

Chaabane

2022

Circuit Theory & Apps

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This paper comes up with a novel fuzzy control design for a wind conversion system (WCS). To do this, a boost converter is employed to adjust the rectified voltage under different wind speed levels. Initially, the boost converter model is well presented via the Takagi-Sugeno approach. Then, a T-S fuzzy controller is designed to promptly calculate the duty cycle required for an optimal power operation. Afterward, the optimal DC current is determined and then transferred to the reference model to instantly determine the desired trajectories. These latter should be preserved so as to reach the maximum power. Following that, linear matrix inequalities (LMIs) are also used to guarantee the stability analyses and the H performance. Finally, the sound performance and the validity of the suggested control schema are both proved by a numerical and some experimental results.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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