• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.5-116
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• 2001

When inertial navigation system(INS) employ more sensors that mutually orthogonal sets to three, the redundant sensor system can have improved reliability and accuracy. For the redundant system the placement of redundant sensors is related to the system performance and also the number and proper orientation of sensors are important. We consider INS sensor configurations using two IMUs comprised mutually orthogonal sets of three. We suggest several configurations using two IMUs and analyze the system performance and the FDI(fault detection and isolation) properties from suggested configurations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.175-189
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• 2023

Fault detection and diagnosis (FDI) algorithms are actively being researched for ensuring the integrity and reliability of environment perception sensors in autonomous vehicles. In this paper, a fault detection algorithm based on a multi-sensor perception system composed of radar, camera, and lidar is proposed to guarantee the safety of an autonomous vehicle's perception system. The algorithm utilizes reference generation filters and residual generation filters based on finite impulse response (FIR) filter estimates. By analyzing the residuals generated from the filtered sensor observations and the estimated state errors of individual objects, the algorithm detects faults in the environment perception sensors. The proposed algorithm was evaluated by comparing its performance with a Kalman filter-based algorithm through numerical simulations in a virtual environment. This research could help to ensure the safety and reliability of autonomous vehicles and to enhance the integrity of their environment perception sensors.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.698-705
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• 2002

The redundant sensor configuration problem of inertial navigation system(INS) is considered and analyzed the navigation and fault detection performance according to various sensor configurations. We considered various kinds of redundant sensor configurations for symmetric, cone, and orthogonal configurations and compare the navigation and fault detection performance for the configurations. We show that the navigation and fault detection performance is not affected by the coordinate change for a fixed configuration.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.155-160
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• 2007

A fault detection and isolation (FDI) problem is considered for inertial sensors, such as gyroscopes and accelerometers and a new FDI method for double faults is proposed using reduced-order parity vector. The reduced-order parity vector (RPV) algorithm enables us to isolate double faults with 7 sensors. Averaged parity vector is used to reduce false alarm and wrong isolation, and to improve correct isolation. The RPV algorithm is analyzed by Monte-Carlo simulation and the performance is given through fault detection probability, correct isolation probability, and wrong isolation probability.

• 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).

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1037-1043
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• 2004

In this paper, a new fault detection and isolation algorithm fur inertial sensor system is proposed. To identify the inertial sensor fault, single antenna GPS receiver is used as an effective redundancy source. To use GPS receiver as redundancy for the inertial sensors, the algorithm to estimate the attitude and acceleration using single antenna GPS receiver is adopted. By using Doppler shift of carrier phase signal and kinetic characteristics of aircraft, attitude information of aircraft can be obtained at the coordinated flight condition. Based on this idea, fault diagnosis algorithm for inertial sensors using single antenna GPS based attitude is proposed. For more effective FDI, decision variables considering the aircraft maneuver are proposed. The effectiveness of the proposed algorithm is verified through the numerical simulations.

• 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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• 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.

• 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.