Fault reconstruction using a Takagi-Sugeno sliding mode observer for the wind turbine benchmark

2014 ◽  
Author(s):  
Florian Poschke ◽  
Soren Georg ◽  
Horst Schulte
Keyword(s):  
Wind Turbine ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Fault Reconstruction ◽  
Takagi Sugeno

Robust actuator and sensor fault reconstruction of wind turbine using modified sliding mode observer

2018 ◽  
Vol 41 (6) ◽  
pp. 1504-1518 ◽  
Author(s):  
Mostafa Rahnavard ◽  
Moosa Ayati ◽  
Mohammad Reza Hairi Yazdi
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Rotational Speed ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Fault Reconstruction ◽  
Different Order ◽  
Aerodynamic Torque

This paper proposes a robust fault diagnosis scheme based on modified sliding mode observer, which reconstructs wind turbine hydraulic pitch actuator faults as well as simultaneous sensor faults. The wind turbine under consideration is a 4.8 MW benchmark model developed by Aalborg University and kk-electronic a/s. Rotor rotational speed, generator rotational speed, blade pitch angle and generator torque have different order of magnitudes. Since the dedicated sensors experience faults with quite different values, simultaneous fault reconstruction of these sensors is a challenging task. To address this challenge, some modifications are applied to the classic sliding mode observer to realize simultaneous fault estimation. The modifications are mainly suggested to the discontinuous injection switching term as the nonlinear part of observer. The proposed fault diagnosis scheme does not require know the exact value of nonlinear aerodynamic torque and is robust to disturbance/modelling uncertainties. The aerodynamic torque mapping, represented as a two-dimensional look up table in the benchmark model, is estimated by an analytical expression. The pitch actuator low pressure faults are identified using some fault indicators. By filtering the outputs and defining an augmented state vector, the sensor faults are converted to actuator faults. Several fault scenarios, including the pitch actuator low pressure faults and simultaneous sensor faults, are simulated in the wind turbine benchmark in the presence of measurement noises. Simulation results show that the modified observer immediately and faithfully estimates the actuator faults as well as simultaneous sensor faults with different order of magnitudes.

scholarly journals An H∞ sliding mode observer for Takagi–Sugeno nonlinear systems with simultaneous actuator and sensor faults An

2015 ◽  
Vol 25 (3) ◽  
pp. 547-559 ◽  
Author(s):  
Ali Ben Brahim ◽  
Slim Dhahri ◽  
Fayçal Ben Hmida ◽  
Anis Sellami
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode ◽  
Design Method ◽  
Estimation Error ◽  
Sliding Mode Observer ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Fault Reconstruction ◽  
The Stability ◽  
Takagi Sugeno

Abstract This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi-Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H∞ performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a sliding mode observer (SMO) with two discontinuous terms to solve the problem of simultaneous faults. Sufficient stability conditions in terms linear matrix inequalities are achieved to guarantee the stability of the state estimation error. The observer gains are obtained by solving a convex multiobjective optimization problem. Simulation examples are given to illustrate the performance of the proposed observer

Robust sliding mode observer design for simultaneous fault reconstruction in perturbed Takagi-Sugeno fuzzy systems using non-quadratic stability analysis

2020 ◽  
Vol 26 (11-12) ◽  
pp. 1092-1105
Author(s):  
Samira Asadi ◽  
Alireza Khayatian ◽  
Maryam Dehghani ◽  
Navid Vafamand ◽  
Mohammad Hassan Khooban
Keyword(s):  
Lyapunov Function ◽  
Fault Detection ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Observer Design ◽  
Performance Criteria ◽  
Linear Matrix ◽  
Quadratic Lyapunov Function ◽  
Fault Reconstruction ◽  
Takagi Sugeno

Appearing faults in a practical system is dispensable, and if it is not compensated, it results in poor system performance or even dysfunction of the system. The fault detection has become a promising challenging issue to guarantee the safety and reliability of systems. In this paper, a novel fuzzy-based sliding mode observer for the simultaneous actuator and sensor fault reconstruction of nonlinear systems subjected to external disturbance is proposed. The proposed approach employs the Takagi-Sugeno fuzzy model, sliding mode observer and non-quadratic Lyapunov function. First, by filtering the system output, a fictitious system whose actuator faults are the original actuator and sensor faults is constructed. Then, by considering the [Formula: see text] performance criteria, the effect of disturbance on the state estimations is minimized. It is proved that the estimations asymptotically converge to their actual values for non-perturbed systems. In the process of designing the observer gains, some transformation matrices are obtained by solving linear matrix inequalities. The proposed approach has some superiority over the existing methods. First, considering the non-quadratic Lyapunov function leads to relaxed results and good estimation performance. Second, using the sliding mode observer makes the proposed approach insensitive to the uncertainties and unknown inputs and determines the shape and size of the fault. Third, assuming the premise variables are immeasurable makes the presented approach more applicable. In conclusion, two practical systems are considered and simulation results illustrate the merits of the proposed approach in comparison with the recent methods from the fast and precise fault detection performance viewpoints.

Robust Fault Identification of Turbofan Engines Sensors Based on Fractional-Order Integral Sliding Mode Observer

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaocong He ◽  
Lingfei Xiao
Keyword(s):  
Fractional Order ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Fault Identification ◽  
Integral Sliding Mode ◽  
Turbofan Engines ◽  
System A ◽  
Fault Reconstruction ◽  
Integral Sliding Surface ◽  
Fractional Order Integral

Abstract This paper presents a robust fault identification scheme based on fractional-order integral sliding mode observer (FOISMO) for turbofan engine sensors with uncertainties. The equilibrium manifold expansion (EME) model is introduced due to its simplicity and accuracy for nonlinear system. A fractional-order integral sliding mode observer is designed to reconstruct faults on sensors, in which the fractional-order integral sliding surface guarantees the fast convergence of reconstruction. The observer parameters is selected according to L2 gain theory in order to minimize the effect of uncertainties on the fault reconstruction signal. Simulations in Matlab/Simulink show high reconstruction accuracy of the proposed method despite the present of uncertainties.

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