• Journal of Power Electronics
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• v.6 no.1
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• pp.8-17
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• 2006

In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1247-1253
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• 2008

A design method of a T-S fuzzy model based reduced order nonlinear unknown input observer(NUIO) is presented. The fuzzy NUIO is designed based on the parallel distributed compensation(PDC) concept. It consists of a number of the linear UIOs, each of which is designed for each local linear model in the T-S fuzzy model of a class of nonlinear systems. The fuzzy NUIO provides not only the state estimates insensitive to the unknown inputs, for example, disturbances and faults etc., but also the estimates of the unknown inputs. Therefore, It can be employed in the state feedback control and disturbance rejection control of a class of nonlinear systems with unknown disturbances. It also applied to the robust residual generation for the fault detection and isolation systems and to the design of fault tolerant control systems. As an example, the NUIO is applied to an inverted pendulum system to show the state and disturbance estimation performance and to illustrate the fuzzy reduced order NUIO design method.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2230-2232
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• 2004

A residual generation scheme that can be employed in the process fault detection and isolation systems for a class of nonlinear (control) systems is suggested. Although the scheme is a kind of observer scheme, the design of the observers employed for residual generation is very simple and the order of the observer is very low. In spite of the simplicity, the residual generation scheme provides the same information for the detection and isolation of the anticipated faults as the conventional multiple observer based schemes. The residuals may be structured so that fault isolation can be performed by pre-selected logic. An FDIS using the residual generation scheme is constructed and evaluated for a nonlinear DC motor system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1145-1153
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• 2011

EMB (Electro-Mechanical Brake) systems can provide improved braking and stability functions such as ABS, EBD, TCS, ESC, BA, ACC, etc. For the implementation of the EMB systems, reliable and robust fault detection algorithm is required. In this study, a model-based fault detection algorithm is designed based on the analytical redundancy method in order to monitor current and force sensor faults in EMB systems. A state-space model for the EMB is derived including faulty signals. The fault diagnosis algorithm is constructed using the analytical redundancy method. Observer is designed for the EMB and the fault detectability condition is examined based on the residual analysis. The performance of the proposed model-based fault detection algorithm is verified in simulations. The effectiveness of the proposed algorithm is demonstrated in various faulty cases.

• Advances in aircraft and spacecraft science
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• v.4 no.1
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• pp.53-64
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• 2017

Aerospace Launch Vehicles (ALV) are generally designed with high reliability to operate in complete security through fault avoidance practices. However, in spite of such precaution, fault occurring is inevitable. Hence, there is a requirement for on-board fault recovery without significant degradation in the ALV performance. The present study develops an advanced fault recovery strategy to improve the reliability of an Aerospace Launch Vehicle (ALV) navigation system. The proposed strategy contains fault detection features and can reconfigure the system against common faults in the ALV navigation system. For this purpose, fault recovery system is constructed to detect and reconfigure normal navigation faults based on the sliding mode observer (SMO) theory. In the face of pitch channel sensor failure, the original gyro faults are reconstructed using SMO theory and by correcting the faulty measurement, the pitch-rate gyroscope output is constructed to provide fault tolerant navigation solution. The novel aspect of the paper is employing SMO as an online tuning of analytical fault recovery solution against unforeseen variations due to its hardware/software property. In this regard, a nonlinear model of the ALV is simulated using specific navigation failures and the results verified the feasibility of the proposed system. Simulation results and sensitivity analysis show that the proposed techniques can produce more effective estimation results than those of the previous techniques, against sensor failures.

• Journal of Power Electronics
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• v.14 no.4
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• pp.695-703
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• 2014

In this paper, a fault detection scheme for DC-link voltage sensor and its fault tolerant control strategy for three-phase AC/DC/AC PWM converters are proposed, where the Luenberger observer is applied to estimate the DC-link voltage. The Luenberger observer is based on a converter model, which is derived from the voltage equations of a grid-side converter and the power balance on a DC link. A fault of the voltage sensor is detected by comparing the measured value of the DC-link voltage with the estimated one. When a sensor fault is detected, a fault tolerant control strategy is performed, where the estimated DC-link voltage is used for the feedback control. The estimation error from the observer is about 1.5 V, which is sufficiently accurate for feedback control. In addition, it is shown that the observer performance is robust to parameter variations of the converter. The validity of the proposed method has been verified by simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.313-323
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• 2014

Sensor fault detection and isolation problems subject to H_/$H_{\infty}$, performance are concerned for linear time-invariant systems with time delay in a state and parametric uncertainties. To that end, a model-based observer bank approach is pursued. The design conditions for both continuous- and discrete-time cases are formulated in terms of matrix inequalities, which are then converted to the problems solvable via an algorithm involving convex optimization.

• 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.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1012-1024
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• 2016

This study deals with an on-line software fault detection, localization, and system reconfiguration method for electrical system drives composed of three-phase AC/DC/AC converters and three-phase permanent magnet synchronous machine (PMSM) drives. Current sensor failure (outage), speed/position sensor loss (disconnection), and damaged DC-link voltage sensor are considered faults. The occurrence of these faults in PMSM drive systems degrades system performance and affects the safety, maintenance, and service continuity of the electrical system drives. The proposed method is based on the monitoring signals of "abc" currents, DC-link voltage, and rotor speed/position using a measurement chain. The listed signals are analyzed and evaluated with the generated residuals and threshold values obtained from a Sliding Mode Current-Speed-DC-link Voltage Observer (SMCSVO) to acquire an on-line fault decision. The novelty of the method is the faults diagnosis algorithm that combines the use of SMCSVO and adaptive thresholds; thus, the number of false alarms is reduced, and the reliability and robustness of the fault detection system are guaranteed. Furthermore, the proposed algorithm's performance is experimentally analyzed and tested in real time using a dSPACE DS 1104 digital signal processor board.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1724-1725
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• 2007

This paper presents a fault detection and isolation(FDI) scheme for a nonlinear systems with a actuator and sensor faults. A residual generator based on the observer model generate the information for a fault detection. The proposed fault estimators are activated for a fault isolation and applied to estimate the time-varying lumped faults(model uncertainty + fault). but a fault estimator error dose not converge to zero since the derivative of lumped fault is not zero. Then the fuzzy neural network(FNN) is used to estimate the fault estimator error. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.