• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.32.3-32
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• 2002

We analyze the effect of main inertial sensor errors such as, misalignment, scale factor error and bias on the performance of modified sequential probability ratio test (SPRT) for sequential fault detection and isolation (FDI). The inertial sensor errors cause the modified SPRT method to give false alarm. We use a two-stage KF to obtain a modified parity vector with which the inertial sensor errors can be removed and thus modified SPRT method can be used regardless of inertial sensor errors.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.880-887
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• 2005

This paper presents a fault diagnosis(detection and isolation) approach for the Ammunition Transport Automation system(ATAS). Due to limited time and information available during its cyclic operation, the on-line fault detection algorithm consists of sequential test logics referring to the normal states, which can be considered as a kind of expert system. If a failure were detected, the off-line isolation algorithm finds the fault location through trained ART2 neural network. By the results of simulations and some on-line field test, it has been shown that the presented approach is effective enough and applicable to related automation systems.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1002-1008
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• 2009

We consider a double faults detection and isolation problem using modified extended parity space approach for inertial measurement unit which use redundant inertial sensors. A redundant IMU which has a hardware redundant is composed of the cone shape because it is good for fault detection and isolation. We analyze the type of double faults and the reason why fault isolation performance is low. We propose modified extended parity space approach method using EPSA and the difference of sensor data.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.308-314
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• 2003

This paper presents a serial communication based fault diagnosis scheme for a brushless DC (BLDC) motor using parameter estimation and Bayes classifier. The presented scheme consists of a smart network board, and a fault detection and isolation (FDI) master. The smart network board is installed near the BLDC motor drive system to acquire motor data and transmit motor data to the FDI-master via serial communication channel. The FDI-master estimates BLDC motor resistance to detect symptom of faults, and assign symptom to fault type using Bayes classifier. In this scheme, since communication time delay has a serious effect on performance, periodic and fixed communication protocol is designed. Hence, the delay time is priory known. By experiment result, presented scheme was verified.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.81-86
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• 2005

In this paper we consider an optimal configuration problem for redundant inertial sensors which have uncertainty such as misalignment, scale factor error. The optimal configuration problem is treated from the viewpoint of navigation accuracy. We propose a necessary and sufficient condition for the optimal configuration of redundant sensors with no uncertainty, and a sufficient condition for the optimal configuration of redundant sensors with uncertainty. Finally we propose a condition for the optimal configuration based both navigation performance and FDI(fault detection and isolation).

• 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.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.115-118
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• 2001

In this paper we propose an FDI(fault detection and isolation) algorithm using neural network-based multi-fault models to detect and isolate single faults in nonlinear systems. When a change in the system occurs, the errors between the system output and the neural network nominal system output cross a threshold, and once a fault in the system is detected, the fault classifier statistically isolates the fault by using the error between each neural network-based fault model output and the system output.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• Journal of IKEEE
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• v.23 no.1
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• pp.266-272
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• 2019

Multicopters have become more popular since they are advantageous in their ability to take off and land vertically. In order to guarantee the normal operations of such multicopters, the problem of fault detection and isolation is very important. In this paper, a new method for detecting and isolating an actuator fault of a hexacopter is proposed based on the analytical approach. The residual is newly defined using the angular velocities of actuators estimated by the mathematical model and an actuator fault is detected comparing the residuals to a threshold. And a fault is isolated combining a dynamic model and generated residuals when a fault is detected. The proposed method is a simple, but effective technique because it is based on mathematical model. The results of the computer simulation are also given to demonstrate the validity of the proposed algorithm in case of a single failure.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.922-927
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• 2002

A variable structure control (VSC) based model following control system that possesses fault detection and isolation (FDI) capability as well as fault tolerance property is proposed. The nonlinear part of the proposed control law. whose magnitude is determined by sliding variables, plays the role of suppressing fault effect. Thus, approximate fault reconstruction is also possible via the analysis of sliding variables. The proposed algorithm is applied to an active suspension system of pound vehicles to verify its applicability.