Design of a proportional integral observer based on sliding mode principle for uncertain Takagi-Sugeno fuzzy systems: applications to a turbo-reactor

2018 ◽  
Vol 12 (2) ◽  
pp. 179
Author(s):  
Ilyes Elleuch ◽  
Atef Khedher ◽  
Kamel Ben Othman
Keyword(s):  
Fuzzy Systems ◽  
Sliding Mode ◽  
Proportional Integral ◽  
Takagi Sugeno

Sliding mode fault-tolerant control for Takagi-Sugeno fuzzy systems with local nonlinear models: Application to inverted pendulum and cart system

2020 ◽  
pp. 014233122094936
Author(s):  
Riadh Hmidi ◽  
Ali Ben Brahim ◽  
Slim Dhahri ◽  
Fayçal Ben Hmida ◽  
Anis Sellami
Keyword(s):  
Fuzzy Systems ◽  
Inverted Pendulum ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Nonlinear Models ◽  
Fault Tolerant Control ◽  
Simultaneous Occurrence ◽  
Sensor Faults ◽  
Adaptive Sliding Mode ◽  
Takagi Sugeno

This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as ‘pseudo-actuator’ faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence of norm-bounded uncertainties. Second, an adaptive sliding mode controller is suggested to provide a solution to stabilize the closed-loop system, even in the event of simultaneous occurrence of faults in actuators and sensors. Next, the main objective of the fault-tolerant control strategy is to compensate for the effects of fault based on the feedback information. Therefore, using the LMI optimization method, sufficient conditions are developed with [Formula: see text] to calculate the gains of the observer and the controller. Then, particular attention is paid to the simultaneous maximization, by convex multi-objective optimization, of the Lipschitz nonlinear constant in Takagi-Sugeno fuzzy modelling and uncertainties attenuation level. The results of the simulation illustrate the effectiveness of our fault-tolerant control approach using a nonlinear inverted pendulum with a cart system.

scholarly journals Controllers Design based on Takagi-Sugeno Fuzzy Systems and Sliding Mode for a Non-Holonomic Mobile robot

2021 ◽  
Author(s):  
hafedh Abid
Keyword(s):  
Mobile Robot ◽  
Fuzzy Systems ◽  
Sliding Mode ◽  
Control Laws ◽  
Kinematic Behavior ◽  
Integral Controller ◽  
Proportional Integral Controller ◽  
The Stability ◽  
Takagi Sugeno ◽  
Holonomic Mobile Robot

Abstract This paper is interesting to a nonholonomic wheeled mobile robot. We have presented a scheme to develop controllers. Two controllers have been developed. The first concerns the kinematic behavior while the second relates to the dynamic behavior of the mobile robot. For the Kinematic controller, we have used a Takagi-Sugeno fuzzy system to overcome the nonlinearities present in model whereas for the second controller we have used the sliding mode approach. The sliding surface has the identical structure as the proportional integral controller. The stability of system has been proved based on Lyapunov approach. The simulation results show the efficiency of the proposed control laws.

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.

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