• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.141-152
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• 2006

This paper presents the development of a decision model to examine the optimal repair action for a deteriorating system. In order to make a reasonable decision, it is necessary to perform an analysis of the uncertainties embedded in deterioration and to evaluate the repair actions based on the expected future cost. Focusing on the power law failure model, the uncertainties related to deterioration are analyzed based on the Bayesian approach. In addition, we develop a decision model for the optimal repair action by applying a repair cost function. A case study is given to illustrate a decision-making process by analyzing the loss incurred due to deterioration.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2319-2324
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• 2005

This paper proposes a intelligent gain and boundary layer based sliding mode control (SMC) method for robotic systems with unknown model uncertainties. For intelligent gain and boundary layer, we employ the self recurrent wavelet neural network (SRWNN) which has the properties such as a simple structure and fast convergence. In our control structure, the SRWNNs are used for estimating the width of boundary layer, uncertainty bound, and nonlinear terms of robotic systems. The adaptation laws for all parameters of SRWNNs and reconstruction error bounds are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with unknown uncertainties. Accordingly, the proposed method can overcome the chattering phenomena in the control effort and has the robustness regardless of unknown uncertainties. Finally, simulation results for the three-link manipulator, one of the robotic systems, are included to illustrate the effectiveness of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.2
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• pp.67-80
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• 1995

In order to control systems which are dominantly subjected to modeling errors and uncertainties, control strategies must deal with the effect of modeling errors and uncertainties. Since most of control methods based on system mathematical model, such as LQG/LTR method, have been developed mainly focused on stability robustness, they can not smartly improve the transient response disturbed by modeling errors and/or uncertainties. In this research, a fuzzy PID control method is suggested, which can stably improve the transient responses of systems disturbed by modeling errors as well as systems not entirely using mathematical models. So as to assure the effectiveness of suggested control method, computer simulations are accomplished for some example systems, through the comparison of transient responses.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.950-955
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• 2014

In this paper, we propose a drug treatment protocol for the three state HIV infection model that explicitly includes the concentration of healthy T cells, infected T cells, and HIV. While most of the previous methods are not able to achieve the treatment goal in the presence of modelling errors, the proposed method is designed so as to compensate for the model uncertainties. Based on the Jacobain linearization of nonlinear HIV infection model, disturbance observer(DOB) based control is employed to design the drug treatment for the HIV patients. Computer simulation is carried out for nonlinear model in order to compare the performance of the proposed method with that of the conventional technique. The simulation results show that, in the presence of parameter uncertainties, the substantial improvement in the performance can be achieved by the proposed DOB controller.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.822-827
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• 2014

This paper presents a robust observer-based output feedback control for stabilization of linear time invariant systems with polytopic uncertainties. To this end, this paper not only finds a robust observer gain but also suggests how to determine the model used in the observer, which is not obvious due to model uncertainties in the conventional observer design method. The robust observer gain and the observer model are selected in a way that the whole closed-loop is stable by solving LMIs and BMIs (Linear Matrix Inequalities and Bilinear Matrix Inequalities). A simulation example shows that the proposed robust observer-based output feedback control successfully leads to closed-loop stability.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2730-2741
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• 1993

A mathematical model of the seeker scan-loop which is composed of a spin-stabilized gyroscope and its driving signal processors is derived. The derived model has a transmission zero pair on the imaginary axis near to the required bandwidth. The LQG/LTR design methodology is evolved for the derived scan-loop model. To implement the designed LQG/LTR compensator to the actual plant, the compensator order is reduced using the internally balanced realization method. The performances of the LQG/LTR compensator are tested and compared with those of the P-control. Especially, stability-robustnessexperiments for model uncertainties represented in the form of time-delays are performed. It is demonstrated that the LQG/STR compensator is actually very robust to model uncertainties.

• Journal of Power Electronics
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• v.19 no.2
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• pp.497-508
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• 2019

The predictive speed control (PSC) strategy can realize the simultaneous control of speed and current by using one cost function. As a model-based control method, the performance of the PSC is vulnerable to model mismatches such as load torque disturbances and parameter uncertainties. To solve this problem, this paper presents a robust predictive speed control (RPSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed RPSC uses extended state observers (ESOs) to estimate the lumped disturbances caused by load torque changes and parameter mismatches. The observer-based prediction model is then compensated by using the estimated disturbances. The introduction of ESOs can achieve robustness against predictive model uncertainties. In addition, a modified cost function is designed to further suppress load torque disturbances. The performance of the proposed RPSC scheme has been corroborated by experimental results under the condition of load torque changes and parameter mismatches.

• IE interfaces
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• v.24 no.4
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• pp.408-419
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• 2011

R&D is a foundation for new business chance and productivity improvement leading to enormous expense and a long-term multi-step process. During the R&D process, decision-makers are confused due to the various future uncertainties that influence economic and technical success of the R&D projects. For these reasons, several decision-making models for R&D project investment have been suggested; they are based on traditional methods such as Discounted Cash Flow (DCF), Decision Tree Analysis (DTA) and Real Option Analysis (ROA) or some fusion forms of the traditional methods. However, almost of the models have constraints in practical use owing to limits on application, procedural complexity and incomplete reflection of the uncertainties. In this study, to make the constraints minimized, we propose a new model named Real Option Decision Tree Model which is a conceptual combination form of ROA and DTA. With this model, it is possible for the decision-makers to simulate the project value applying the uncertainties onto the decision making nodes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.3-6
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• 2000

The magnetic bearing system are intrinsically unstable, and need the feedback control of electromagnetic forces with measured displacements. So the controller design plays an important role in constructing high performance magnetic bearing system. In case of magnetic bearing system, the order of identified model is high because of unknown dynamics included in closed loop systems - such as sensor dynamics, actuator dynamics - and non-linearity of magnetic bearings itself. In this paper the identification and robust control of flexible rotor supported by magnetic bearing are discussed. We measure and identify overall system that contains not only flexible rotor model but also magnetic bearing and time delay. The structured and unstructured uncertainties are modeled that cover variations of natural frequencies, uncertainties in sensor and actuator gains and unmodeled dynamics. And desired performances are specified with several weighting function. Using augmented system that includes identified model, uncertainties, and weighting functions, μ-synthesis is applied to flexible rotor supported with magnetic bearing. The flexible rotor was spin up over the first flexible critical speed.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.