New Observer Design Conditions for Takagi-Sugeno Fuzzy Systems

2018 ◽  
Author(s):  
Jun Yoneyama ◽  
Yuto Takenaka ◽  
Kenta Hoshino
Keyword(s):  
Fuzzy Systems ◽  
Observer Design ◽  
Takagi Sugeno

scholarly journals Adaptive Proportional Integral Observer Design for Interval Type 2 Takagi–Sugeno Fuzzy Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Atef Khedher ◽  
Ilyes Elleuch ◽  
Kamal BenOthman
Keyword(s):  
Fuzzy Systems ◽  
Observer Design ◽  
Adaptive Observer ◽  
Fault Estimation ◽  
Sensor Faults ◽  
Proportional Integral ◽  
Augmented State ◽  
Interval Type ◽  
Takagi Sugeno

In this paper, the problem of fault estimation in systems described by Takagi–Sugeno fuzzy systems is studied. A proportional integral observer is conceived in order to reconstruct state and faults which can affect the studied system. Proportional integral observer can easily estimate actuator faults which are assimilated to be as unknown inputs. In order to estimate actuator and sensor faults, a mathematical transformation is used to conceive an augmented system, in which the initial sensor fault appears as an unknown input. Considering the augmented state, it is possible to conceive an adaptive observer which is able to estimate the whole state and faults. The noise effect on the state and fault estimation is also minimized in this study, which provides some robustness properties to the proposed observer. The proportional integral observer is conceived for nonlinear systems described by Takagi–Sugeno fuzzy models.

scholarly journals Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
N. El Youssfi ◽  
R. El Bachtiri ◽  
T. Zoulagh ◽  
H. El Aiss
Keyword(s):  
Fuzzy Systems ◽  
Sufficient Conditions ◽  
State Equation ◽  
Observer Design ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Vehicle Model ◽  
Lateral Dynamics ◽  
Takagi Sugeno ◽  
Vehicle Lateral Dynamics

This paper deals with the problem of observer design of the vehicle model which is represented by Takagi–Sugeno (T–S) fuzzy systems with the presence of uncertainties. A relaxed observer design is presented to estimate the unmeasurable states and the faults of the vehicle lateral dynamics model, simultaneously. The vehicle model is transformed into a system with unknown inputs. Then, it is rebuilt by adding the default to the system state equation. Based on the Lyapunov function approach and the introduction of some slack variables, sufficient conditions of unknown input observer design are formulated as Linear Matrix Inequalities (LMIs). Finally, the simulation section clearly shows the importance and effectiveness of the proposed strategy.

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