• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1440-1443
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• 1997

The optimal residual generator based on parity relation approach for the fault detection and isolation of a arge diesel engine actuator position servo system is presented. The closed-loop residual generator is designed to have robustness against modeling errors and noise. Main purpose of the fault detection and isolation system in the process is to detect and isolate two important faults, i.e., actuatro fault and fault of speed sensor, that, if not detected and compensated, degrade the overall control system performance. Simulation results are give to show the practical applicability of the fault detecrtion and isloation scherme.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.54-63
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• 2016

A novel attitude tacking control method using Time Delay Control (TDC) scheme is developed to provide robust controllability of a rigid hexacopter in case of single or multiple rotor faults. When the TDC scheme is developed, the rotor faults such as the abrupt and/or incipient rotor faults are considered as model uncertainties. The kinematics, modeling of rigid dynamics of hexacopter, and design of stability and controllability augmentation system (SCAS) are addressed rigorously in this paper. In order to compare the developed control scheme to a conventional control method, a nonlinear numerical simulation has been performed and the attitude tracking performance has been compared between the two methods considering the single and multiple rotor faults cases. The developed control scheme shows superior stability and robust controllability of a hexacopter that is subjected to one or multiple rotor faults and external disturbance, i.e., wind shear, gust, and turbulence.

• Advances in robotics research
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• v.2 no.1
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• Smart Structures and Systems
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• v.16 no.2
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• pp.329-345
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• 2015

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order $H_{\infty}$ FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

• Smart Structures and Systems
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• v.8 no.5
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• pp.501-524
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• 2011

Recent studies have discovered that a conventional passive isolation system may suffer from an excessive isolator displacement when subjected to a near-fault earthquake that usually has a long-period velocity pulse waveform. Semi-active isolation using variable friction dampers (VFD), which requires a suitable control law, may provide a solution to this problem. To control the VFD in a semi-active isolation system more efficiently, this paper investigates experimentally the possible use of a control law whose control logic is similar to that of the anti-lock braking systems (ABS) widely used in the automobile industry. This ABS-type controller has the advantages of being simple and easily implemented, because it only requires the measurement of the isolation-layer velocity and does not require system modeling for gain design. Most importantly, it does not interfere with the isolation period, which usually decides the isolation efficiency. In order to verify its feasibility and effectiveness, the ABS-type controller was implemented on a variable-friction isolation system whose slip force is regulated by an embedded piezoelectric actuator, and a seismic simulation test was conducted for this isolation system. The experimental results demonstrate that, as compared to a passive isolation system with various levels of added damping, the semi-active isolation system using the ABS-type controller has the better overall performance when both the far-field and the near-fault earthquakes with different PGA levels are considered.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.

• 대한공업교육학회지
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• v.34 no.2
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• pp.396-410
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• 2009

The goal of this work is to present an advanced method of an estimation of the Modeling Uncertainties coming up in industrial rigid robot's manipulator and actuators. First, with the given physical robot model, the motion equation was derived. Considering a fictitious model, a new extended motion equation is developed. Based on this extended model, an observer and observer bank are designed for the estimation of modeling uncertainties which are involving the effects of gravity, friction, mass unbalance, and Coriolis which show the nonlinear characteristics in operation states.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.