Finite-Frequency Model Reduction of Takagi–Sugeno Fuzzy Systems

2016 ◽  
Vol 24 (6) ◽  
pp. 1464-1474 ◽  
Author(s):  
Da-Wei Ding ◽  
Xiao-Jian Li ◽  
Xin Du ◽  
Xiangpeng Xie
Keyword(s):  
Model Reduction ◽  
Fuzzy Systems ◽  
Finite Frequency ◽  
Frequency Model ◽  
Takagi Sugeno

scholarly journals Finite frequency model reduction for 2-D fuzzy systems in FM model

2021 ◽  
Vol 297 ◽  
pp. 01035
Author(s):  
Rachid Naoual ◽  
Abderrahim El-Amrani ◽  
Ismail Boumhidi
Keyword(s):  
Model Reduction ◽  
State Space ◽  
Linear Matrix Inequalities ◽  
Fuzzy Systems ◽  
Linear Matrix ◽  
Two Dimensional ◽  
Matrix Inequalities ◽  
Finite Frequency ◽  
Frequency Model ◽  
Takagi Sugeno

This paper deals with the problem of H∞ model reduction for two-dimensional (2D) discrete Takagi-Sugeno (T-S) fuzzy systems described by Fornasini-Marchesini local state-space (FM LSS) models, over finite frequency (FF) domain. New design conditions guaranteeing the FF H∞ model reduction are established in terms of Linear Matrix Inequalities (LMIs). To highlight the effectiveness of the proposed H∞ model reduction design, a numerical example is given.

H∞ model reduction design in finite frequency ranges for discrete-time Takagi-Sugeno fuzzy systems

2021 ◽  
Vol 11 (2) ◽  
pp. 89
Author(s):  
Abderrahim El Amrani ◽  
Bensalem Boukili ◽  
Ahmed El Hajjaji ◽  
Ismail Boumhidi ◽  
Abdelaziz Hmamed
Keyword(s):  
Model Reduction ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Finite Frequency ◽  
Takagi Sugeno

scholarly journals Model Reduction H∞ Finite Frequency of Takagi-Sugeno Fuzzy Systems

2021 ◽  
Vol 6 (5) ◽  
pp. 53-58
Author(s):  
Rim Mrani Alaoui ◽  
Abderrahim El-Amrani ◽  
Ismail Boumhidi
Keyword(s):  
Model Reduction ◽  
Fuzzy Systems ◽  
Finite Frequency ◽  
Takagi Sugeno

scholarly journals New approach to finite frequency Filter Design for two-dimensional T-S fuzzy systems

2021 ◽  
Vol 297 ◽  
pp. 01036
Author(s):  
Ben Meziane Khaddouj ◽  
Abderrahim El-Amrani ◽  
Ismail Boumhidi
Keyword(s):  
Fuzzy Systems ◽  
Filter Design ◽  
Asymptotically Stable ◽  
Two Dimensional ◽  
Finite Frequency ◽  
New Approach ◽  
Filter Model ◽  
Error System ◽  
Non Linear Systems ◽  
Takagi Sugeno

This paper considers the problem of filter design for two-dimensional (2D) discrete-time non-linear systems in Takagi-Sugeno (T-S) fuzzy mode. The problem to be solved in the paper is to find a H∞ filter model such that the filtering error system is asymptotically stable. A numerical example is employed to illustrate the validity of the proposed methods.

H∞ model reduction of discrete-time 2D T-S fuzzy systems in finite frequency ranges

2021 ◽  
Vol 37 (1) ◽  
pp. 22
Author(s):  
Ismail Boumhidi ◽  
Abderrahim El Amrani ◽  
Ahmed El Hajjaji ◽  
Bensalem Boukili
Keyword(s):  
Model Reduction ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Finite Frequency

Improved finite frequency H∞ filtering for Takagi-Sugeno fuzzy systems

2020 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Abdelaziz Hmamed ◽  
Ismail Boumhidi ◽  
Abderrahim El Amrani ◽  
Ahmed El Hajjaji
Keyword(s):  
Fuzzy Systems ◽  
Finite Frequency ◽  
Takagi Sugeno

Finite-frequency model reduction of discrete-time T–S fuzzy state-delay systems

2016 ◽  
Vol 203 ◽  
pp. 121-128 ◽  
Author(s):  
Da-Wei Ding ◽  
Xiangpeng Xie ◽  
Xin Du ◽  
Xiao-Jian Li
Keyword(s):  
Model Reduction ◽  
Discrete Time ◽  
Delay Systems ◽  
Finite Frequency ◽  
Frequency Model ◽  
State Delay ◽  
Fuzzy State

scholarly journals Model reduction design for continuous systems with finite frequency specifications

2021 ◽  
Vol 11 (5) ◽  
pp. 3956
Author(s):  
Miloud Koumir ◽  
Abderrahim El-Amrani ◽  
Ismail Boumhidi
Keyword(s):  
Model Reduction ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Continuous Systems ◽  
Asymptotically Stable ◽  
Matrix Inequalities ◽  
Finite Frequency ◽  
Error System ◽  
Takagi Sugeno

<p>This paper is concerned with the problem of model reduction design for continuous systems in Takagi-Sugeno fuzzy model. Through the defined FF H∞ gain performance, sufficient conditions are derived to design model reduction and to assure the fuzzy error system to be asymptotically stable with a FF H∞ gain performance index. The explicit conditions of fuzzy model reduction are developed by solving linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.</p>

scholarly journals Improved filtering H∞ finite frequency of Takagi-Sugeno fuzzy systems

2021 ◽  
Vol 12 (4) ◽  
pp. 2523
Author(s):  
Rim Mrani Alaoui ◽  
Abderrahim El-Amrani
Keyword(s):  
Fuzzy Systems ◽  
Filter Method ◽  
Linear Matrix ◽  
Fuzzy Filter ◽  
Finite Frequency ◽  
Filter Model ◽  
Error System ◽  
Takagi Sugeno ◽  
Finsler’S Lemma ◽  
Slack Matrices

The work treats the filter H∞ finite frequency (FF) in Takagi-Sugeno (T-S) two dimensional (2-D) systems described by Fornasini-Marchesini local state-space (FM LSS)models. The goal of this work is to find an FF H∞ T-S fuzzy filter model design in such a way that the error system is stable and has a reduced FF H∞ performance over FF area swith noise is established as aprerequisite. Via the use of the generalized Kalman Yakubovich Popov (gKYP) lemma, Lyapunov functions approach, Finsler’s lemma, and parameterize slack matrices, new design conditions guaranteeing the FF H∞ T-S fuzzy filter method of FM LSS models are developed by solving linear matrix inequalities (LMIs). At last, the simulation results are provided to show the effectiveness and the validity of the proposed FF T-S fuzzy of FM LSS models strategy by a practical application has been made.

Sign in / Sign up

Export Citation Format

Share Document