• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.28-37
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• 2013

This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used fault-tolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2582-2587
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• 2003

This paper proposes an application of sliding mode observer to the problem of fault detection and reconstruction for descriptor systems with both actuator and sensor faults. In detecting and reconstructing the faults simultaneously, first, we will consider the fault detection problem for sensor fault. The detection of sensor fault is achieved from the design of the matrix which eliminates the influence of actuator fault. Secondly, the sliding mode observer which adds the general full-order observer for descriptor system to feedforward injection map and feedforward compensation signal is designed, and through which the sensor fault is reconstructed. Finally, with the reconstructed sensor fault, and by eliminating differential term of the sensor fault, the actuator fault is detected and reconstructed.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.41-47
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• 1997

Fault diagnosis problem is currently a subject of extensive research in the control field. Although there are several works on the fault detection and isolation observers and the residual generators, those are con- cerned with only the detection of actuator failures or sensor failures. So, the perfect detection and isolation for the actuator and sensor failures is strongly required in the field of the practical applications. In this paper, a strategy of fault diagnosis using multiple proportional integral (PI) observers including the magnitude of actuator failures is provided. It is shown that actuator failures are detected and isolated perfectly by monitoring the integrated error between actual output and estimated output by a PI observer. Also in presence of complex actuator and sensor failures, these failures are detected and isolated by multiple PI observers.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.130-130
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control lot the actuator and sensor faults in the closed-loop systems affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the residual set generation by using robust Parity space approach. Residual set is evaluated through the threshold test and then fault is isolated according to the decision logic table. Once the fault diagnosis module indicates which actuator or sensor is faulty, the fault magnitude is estimated by using the disturbance-decoupled optimal state estimation and a new additive control law is added to the nominal one to override the fault effect on the system. Simulation results show that the method has definite fault diagnosis and fault tolerant control ability against actuator and sensor faults.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.287-290
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• 1996

Fault diagnosis problem is currently the subject of extensive research and numerous survey paper can be found. Although several works are studied on the fault detection and isolation observers and the residual generators, those are concerned with only the detection of actuator failures or sensor failures. So, the perfect detection and isolation is strongly required for practical applications. In this paper, a, strategy of fault diagnosis using multiple proportional integral (PI) observers including the magnitude of actuator failures is provided. It is shown that actuator failures are detected and isolated perfectly by monitoring the integrated error between actual output and estimated output by a PI observer. Also in presence of complex actuator and sensor failures, these failures are detected and isolated by multiple PI observers.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.272-275
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• 1992

A novel fault diagnosis method based on likelihood decomposition is proposed for linear stochastic systems described by autoregressive (AR) model. Assuming that at some time instant .tau. the fault of one of the following two types is occurs: innovation fault (actuator fault); and observation fault (sensor fault), the log-likelihood function is decomposed into two components based on the observations before and after .tau., respectively, Then, the type of the fault is determined by comparing the log-likelihoods corresponding two types of faults. Numerical examples demonstrate the usefulness of the proposed diagnosis method.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.171-179
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• 2003

In this paper a neural network-based fault tolerant control system for aircraft sensor and actuator failures is considered. By exploiting flight dynamic relations a set of neural networks is constructed to detect sensor failure and give alternative signal for the faulty sensor. For actuator failures another set of neural networks is designed to perform fault detection, identification, and accomodation which returns the aircraft to a new stable trim. Integrated system is simulated to show the performance of the system with sensor and control surface failures.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.4
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• pp.880-888
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• 2001

This paper presents a fault detection asnd isolation algorithm for highly reliable gantry crane system. The algorithm is constructed by multiple PI observer technique, and the magnitude of actuator fault can be estimated by using integrated estimated output error. Also, the complex actuator and /or sensor fault can be detected and isolated by monitoring the integrated error and the estimated state error. Considering the actuator and/or the sensor fault, we verify that these fault can be detected and isolated through simulation. Lastly, we show a simple reliable control method by using the detected fault signal and an added observer.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.6
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• pp.9-16
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• 2007

This paper describes the design and implementation of the fault diagnosis on the Electronic Throttle Control(ETC) System. The proposed fault diagnosis consists of an input signal, actuator and a processor diagnosis. The input signal diagnosis can detect the faults of the ETC system's input signals such as the position sensor fault, source voltage fault, load current fault, and desired position fault. The actuator diagnosis is able to detect the actuator fault due to the actuator aging and an obstacle which interfere in the movement of the actuator. The processor diagnosis detects the fault which prevents the microprocessor from operating the ETC software. In order to protect the breakdown of the ETC system and assure the driving safety, appropriate reactions are also proposed according to the detected faults. The safety and reliability of the ETC system can be improved by the proposed fault diagnosis.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1117-1124
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• 2011

An integrated fault detection and isolation method is proposed in this paper. The main objective of this paper is development fault detection, isolation and diagnosis algorithm based on the DKF (Decentralized Kalman Filter) and the bank of IMM (Interacting Multiple Model) filters using penalty scalar for both partial and total faults and the outlier detection algorithm for preventing false alarm also included. The proposed FDI (Fault Detection and Isolation) scheme is developed in four phases. In the first phase, the outlier detection filter is designed to prevent false alarm as a pre-filter. In the second phases, two local filters and master filter are designed to detect sensor faults. In the third phases, the proposed FDI scheme checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the last phases, four filters are designed to identify the fault type which is either the total fault or partial fault. The developed scheme can deal with not only sensor and actuator faults, but also preventing false alarm. An important feature of the proposed FDI scheme can decreases fault isolation time and figure out not only fault detection and isolation but also fault type identification. To verify the proposed FDI algorithm performance, the Simulator is also developed under the Matlab/Simulink environment.