Actuator and sensor faults estimation for fractional-order linear system via sliding mode observer

Author(s):  
Nadia Djeghali ◽  
Maamar Bettayeb ◽  
Said Djennoune ◽  
Jean-Pierre Barbot ◽  
Malek Ghanes
2018 ◽  
Vol 41 (6) ◽  
pp. 1504-1518 ◽  
Author(s):  
Mostafa Rahnavard ◽  
Moosa Ayati ◽  
Mohammad Reza Hairi Yazdi

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shulan Kong ◽  
Mehrdad Saif ◽  
Guozeng Cui

This study investigates estimation and fault diagnosis of fractional-order Lithium-ion battery system. Two simple and common types of observers are designed to address the design of fault diagnosis and estimation for the fractional-order systems. Fractional-order Luenberger observers are employed to generate residuals which are then used to investigate the feasibility of model based fault detection and isolation. Once a fault is detected and isolated, a fractional-order sliding mode observer is constructed to provide an estimate of the isolated fault. The paper presents some theoretical results for designing stable observers and fault estimators. In particular, the notion of stability in the sense of Mittag-Leffler is first introduced to discuss the state estimation error dynamics. Overall, the design of the Luenberger observer as well as the sliding mode observer can accomplish fault detection, fault isolation, and estimation. The effectiveness of the proposed strategy on a three-cell battery string system is demonstrated.


Author(s):  
Xiaocong He ◽  
Lingfei Xiao

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.


Author(s):  
Cheng Cheng ◽  
Songyong Liu ◽  
Hongzhuang Wu

This paper proposes an observer-based sliding mode control method for electro-hydraulic servo systems with uncertain nonlinearities, external disturbances, and immeasurable states. The mathematical model is built based on the principle of electro-hydraulic servo systems. Owing to its highly robustness and finite time properties, the sliding mode observer is chosen and designed to estimate the velocity and the equivalent pressure online only using the position feedback. Then, in order to tackle the chattering problem of conventional sliding mode control and increase the control accuracy, a novel second-order sliding mode control scheme is proposed based on the fractional-order proportional–integral–derivative sliding surface and the state observer. The stability of the overall system is proved by Lyapunov theory. Finally, the detailed simulations are conducted, which include the comparative analysis of control performance with other methods and the study of observation performance.


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