scholarly journals A new approach to fuzzy estimation of Takagi–Sugeno model and its applications to optimal control for nonlinear systems

2012 ◽  
Vol 12 (1) ◽  
pp. 280-290 ◽  
Author(s):  
Basil M. Al-Hadithi ◽  
Agustín Jiménez ◽  
Fernando Matía
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
New Approach ◽  
Sugeno Model ◽  
Takagi Sugeno

Fuzzy optimal control using generalized Takagi–Sugeno model for multivariable nonlinear systems

2015 ◽  
Vol 30 ◽  
pp. 205-213 ◽  
Author(s):  
Basil Mohammed Al-Hadithi ◽  
Agustín Jiménez ◽  
Ramón Galán López
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Sugeno Model ◽  
Takagi Sugeno ◽  
Multivariable Nonlinear Systems

Fuzzy horizon group shift FIR filtering for nonlinear systems with Takagi–Sugeno model

2016 ◽  
Vol 174 ◽  
pp. 1013-1020 ◽  
Author(s):  
Jung Min Pak ◽  
Choon Ki Ahn ◽  
Chang Joo Lee ◽  
Peng Shi ◽  
Myo Taeg Lim ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Fir Filtering ◽  
Sugeno Model ◽  
Takagi Sugeno ◽  
Group Shift

scholarly journals An interval observer design for uncertain nonlinear systems based on the T-S fuzzy model

2017 ◽  
Vol 27 (3) ◽  
pp. 397-407 ◽  
Author(s):  
Yamina Menasria ◽  
Hichem Bouras ◽  
Nasreddine Debbache
Keyword(s):  
Nonlinear Systems ◽  
Estimation Error ◽  
Fuzzy Model ◽  
Observer Design ◽  
Pole Placement ◽  
Dynamic State ◽  
New Approach ◽  
Dynamic State Estimation ◽  
Interval Observer ◽  
Takagi Sugeno

AbstractA new approach to build an interval observer for nonlinear uncertain systems is presented in this paper. Nonlinear systems modeled in the Takagi-Sugeno (T-S) form are studied. A T-S proportional observer is first issued by pole-placement and LMI tools. Secondly, time-varying change of coordinates for each dynamic state estimation error is used to design an interval observer. The system state bounds are then directly deduced.

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