Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model

Youssef, Tarek; Chadli, Mohammed; Karimi, Hamid Reza; Wang, Rongrong

doi:10.1016/j.jfranklin.2016.09.020

Cited by 238 publications

(128 citation statements)

References 28 publications

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“…For sensor faults, output‐residual–based FDI schemes were presented in the works of Shen et al, Li et al, and Wang et al However, most of the previous studies assume that no more than one sensor fails at a time, whereas this study focuses on multisensor faults, which is more general and committed to managing their combinatorial effects. Different from actuator faults, the majority of sensor faults are often estimated through augmentation methods, which can simultaneously cope with system states and sensor faults . This study adopts an augmented observer to estimate multiple sensor faults simultaneously, considering the interaction of faulty sensors.…”

Section: Introductionmentioning

confidence: 99%

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Chen

Gong

2019

Intl J Robust & Nonlinear

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Summary This study proposes an improved adaptive fault diagnosis and compensation scheme for multisensor faults of hypersonic flight vehicles (HFVs). The faults are detected and isolated through a series of sensor output residuals and thresholds that consider observation error and disturbances. Via an adaptive augmented observer, the faults are estimated accurately and a time‐varying disturbance is handled by an additional differential part. Sensor faults are compensated on the basis of estimation results, and disturbances are considered in the fault‐tolerant control (FTC) design, thereby improving the tracking accuracy of the altitude and velocity and robustness with respect to external disturbances for HFVs. The stability of diagnosis and FTC is analyzed by Lyapunov theory. Numerical simulation results explain the validity of the proposed diagnosis and compensation methods.

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Section: Introductionmentioning

confidence: 99%

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Chen

Gong

2019

Intl J Robust & Nonlinear

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“…is an effective method to solve the problem of nonlinear system control [9]. A proportional integral observer based on T-S fuzzy control is designed for the fault estimation of the actuator and sensor in [10]. Through the Lyapunov stability theory and L 2 performance analysis, the sufficient design conditions for simultaneous estimation of two kinds of faults are given, and the proposed conditions are solved under linear matrix inequalities constraints and the proportional integral observer gains are calculated.…”

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Control Strategy of a Wind Energy Conversion System Considering Multiple Fault Reconstruction

Shen

2018

Applied Sciences

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A robust sliding mode observer (SMO) is proposed to achieve multiple fault reconstruction for a wind energy conversion system (WECS) with simultaneous actuator and sensor faults. Firstly, the state equation of the WECS is established. The orthogonal transformation matrix and a post filter are introduced, and a new augmented system is constructed; then, the sensor fault is converted into an actuator fault to diagnose. The fault information is collected by the equivalent output control, and the simultaneous reconstruction algorithm of the sensor fault and the actuator fault is given. Through compensation control, the reliable control input of the WECS is guaranteed, and the function of active fault tolerant control for multiple faults is achieved. Simulation experiments show that the proposed method can accurately reconstruct the actuator and sensor faults, and maximum wind energy capture can be achieved by active fault-tolerant control.

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“…Fuzzy sets are suitable for solving fault diagnosis problems with uncertain information. Hence, fuzzy approaches have been widely applied to fault diagnosis processes [2][3][4][5][6]. However, it may be difficult to exactly quantify the membership degree in the fuzzy set as an exact value in the interval [0, 1].…”

Section: Introductionmentioning

confidence: 99%

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

2018

Information

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Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs) are very suitable for expressing imprecise or uncertain fault information in real problems. However, existing literature scarcely deals with fault diagnosis problems, such as gasoline engines and steam turbines with IVFSs. However, the similarity measure is one of the important tools in fault diagnoses. Therefore, this paper proposes a new similarity measure of IVFSs based on logarithmic function and its fault diagnosis method for the first time. By the logarithmic similarity measure between the fault knowledge and some diagnosis-testing samples with interval-valued fuzzy information and its relation indices, we can determine the fault type and ranking order of faults corresponding to the relation indices. Then, the misfire fault diagnosis of the gasoline engine and the vibrational fault diagnosis of a turbine are presented to demonstrate the simplicity and effectiveness of the proposed diagnosis method. The fault diagnosis results of gasoline engine and steam turbine show that the proposed diagnosis method not only gives the main fault types of the gasoline engine and steam turbine but also provides useful information for multi-fault analyses and predicting future fault trends. Hence, the logarithmic similarity measure and its fault diagnosis method are main contributions in this study and they provide a useful new way for the fault diagnosis with interval-valued fuzzy information.

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Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model

Cited by 238 publications

References 28 publications

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Fault-Tolerant Control Strategy of a Wind Energy Conversion System Considering Multiple Fault Reconstruction

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

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