• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.138-145
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control method for the control systems in closed-loop affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the disturbance-decoupled state estimation using a 2-stage state observer for state, actuator bias and sensor bias. The estimated bias show the occurrence time, location and type of the faults directly. The estimated state is used for state feedback to achieve fault tolerant control against the faults. Simulation results show that the method has definite fault tolerant ability against actuator and sensor faults, moreover, the faults can be detected on-line, isolated and estimated simultaneously.

• 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 the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.104-109
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• 1997

A robust controller design to corrdinate a robot manipulator under unknown system parameters and bounded disturbance inputs is presented in this paper. Generally, robust controllers require high input torque so that they may face input saturation in actual application due to the power limitation of the actuator. To solve this problem, an improved robust controller with saturated input torque using a fuzzy logic control is proposed. Numerical examples are shown to validate the proposed controller using two degree-of-freedom planar arm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1844-1851
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• 2007

This paper presents methods for the compensation of sinusoidal disturbances with unknown amplitude, phase, and time-varying frequency in nonlinear systems. In the previous disturbance accommodation methods, the sinusoidal disturbance with unknown time-invariant frequency was considered. In the proposed method, the disturbance with unknown time-varying frequency is compensated. As for the control structure, two control inputs are designed separately in such a way that one of them is designed for the nonlinear system control without considering the disturbance, and the other one uses the disturbance estimate obtained from the disturbance accommodating observer. The stability analysis is done considering the disturbance estimation error and the numerical simulation demonstrates the proposed approach.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.58-65
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• 1994

A recursive on-line algorithm for orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters time delay and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursiveform by using new functions of two dimensional autocorrelations and crosscorrelations of inputs and outputs. This proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.58-63
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• 1993

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters, time delay, and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursive form by using new functions of two dimensional autocorrelations and cross-correlations of inputs and outputs. The proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.518-521
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• 1995

In this paper, a learning control problem is formulated for cooperating multiple-robot manipulators with uncertain system parameters. The commonly held object is also assumed to be unknown and the multiple-robots themselfs experience uncertain operating conditions such as link parameters, viscous friction parameters, suctions, actuator bias, and etc. Under these conditions, the learning controllers designed for learning of uncertain parameters and robot control inputs for multiple-robot systems are shown to drive the multiple-robot manipulators to follow the desired Cartesian trajectory with the desired internal forces to the unknown object.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.101-106
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• 2008

This paper deals with the unknown input estimation for linear dynamic systems with sensor noise. The presented method based on the integral observer permits to achieve good convergence and exact estimation of unknown inputs. The validity of proposed method is established by comparison with simulation results and the existing methods.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.927-930
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• 1992

VSS identification approach is based on following concept, i.e. while in sliding motion, the switching of control inputs refects system uncertainites. Therefore, if there exist some operations that make the information form the switiching control inputs be achievable, then the unknown parameters can be actually identification mechanisms which can fully make use of the available information. Two different types of VSS identifiers are taken into consideration. The first type uses adjustable model whose structure is similar to that of identified systems. From the viewpoint of contro, this type of VSS identifiers may be regraded as direct identifier vecause the identified system is handled as an open loop. On the other hand, if the identified system is controlable in the sense of VSS(sliding mode can be generated through chosing control inputs), the second type of VSS identifier, the indirect VSS identifier, can be constructed according to the linerized system strucutre while staying in sliding mode. Therefroe it can be applied to some nonlinear systems which are not linear in parametric space by general identification algorithms, whereas linear in parametric space when sliding mode is existed.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.510-513
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• 1986

In recent years the Kalman filter(extended Kalman filter) have been applied to a wide variety of tracking moving targets, because of its properties. For such a reason, in this paper we attempt to study on adaptive filter algorithms which estimate unknown bias maneuvering inputs.