• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.65-71
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• 1997

In this paper, we propose a new .mu.-controller design method using an equivalent weighting function $W_{\mu}$(s). The proposed mehtod is not guaranteed to converge to the minimum as D-K and .mu.-K iteration method. However, the robust performance problem can be converted into an equivalent $H^{\infty}$ optimization problem of unstructured uncertainty by using an equivalent weightng function $W_{\mu}$(s). Also we can find a .mu.-optimal controller iteratively using an error index $d_{\epsilon}$ of differnce between maximum singular value and .mu.-norm. And under the condition of the same order of scaling functions, the proposed method provides the .mu.-optimal controller with the degree less than that obtained by D-K iteration..

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.878-886
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• 2004

Uncertainties are inevitable in robotic assembly in unstructured environment since it is difficult to construct fixtures to guide motions of robots. This paper proposes an augmented Petri net and an algorithm to adapt the assembly model on-line during actual assembly process. The augmented Petri net identifies events using force and position information simultaneously. Unmodeled contact states are identified and incorporated into the model on-line. The proposed method increases the level of intelligence of the robot system by enhancing the autonomy. The proposed method is evaluated by simulation and experiments with L-type peg-in-hole assembly using a two-arm robot system.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.130-140
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• 2003

This paper presents an $H_\infty$controller synthesis based on disturbance observer for the trajectory control of a hydraulic excavator. Compared to conventional robot manipulators driven by electrical motors, hydraulic excavator have more nonlinear and coupled dynamics. In particular, the interactions between an excavation tool and the materials being excavated are unstructured and complex. In addition, its operating modes depend on working conditions, which make it difficult to not only derive the exact mathematical model but also design a controller systematically. In this study, the approximated linear model obtained through off-line system identification is used as nominal plant model for a disturbance observer. A disturbance observer based tracking controller which considers the effect of disturbance and model uncertainty is synthesized in $H_\infty$frameworks. Simulation results are used to demonstrate the applicability of the proposed control scheme.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.131-138
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• 1996

In this paper, we consider an iterative learning control system(ILCS) consisting of an iterative learning controller, a feedback controller and a controlled plant in the frequency domain. At first, we review the convergence of ILCS. And we give some design guidelines of the ILCS using a nominal model of the plant. Then we present the structured and the unstructured uncertainty bound which guarantees the convergence of the designed iterative learning controller. In particular, we analyze the relationship between the convergence and the magnitude and phase uncertainties. In order to show the usefulness of the proposed analysis and design guidelines, we present some simulation examples. (author). 13 refs., 5 figs.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.178-189
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• 1995

In this pater, authors derive the state - space equiation about the patallel - type inverted pendulum which is adopted as control object, and constitute the control system by $H_\infty$control theory. The modeling error is unavoidably existed by linearization error, and so on. We regard this modeling error which is determined from the identification through frequency response as unstructured model uncertainty. An augmented state - space equiation with frequency weighting function is constructed for application of the $H_\infty$theory, and the mixed sensitivity problem is considered. The weighting functions are determined in consideration of the model uncertainty and the response of system in frequency region. The $H_\infty$controller is designed by using software package for controller design. From results of response simulation, the control system designed with $H_\infty$theory guarantees low sensitivity for disturbance as well as robustness against the model uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.552-557
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• 2004

This paper presents a disturbance observer based on an $H_{\infty}$ controller synthesis for the trajectory control of a hydraulic excavator. Compared to conventional robot manipulators driven by electrical motors, the hydraulic excavator has more nonlinear and coupled dynamics. In particular, the interactions between an excavation tool and the materials being excavated are unstructured and complex. In addition, its operating modes depend on working conditions, which make it difficult to not only derive the exact mathematical model but also design a controller systematically. In this study, the approximated linear model obtained through off-line system identification is used as nominal plant model for a disturbance observer. A disturbance observer based tracking controller which considers the effect of disturbance and model uncertainty is synthesized in $H_{\infty}$ frameworks. Simulation results are used to demonstrate the applicability of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.316-321
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• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• Journal of Sensor Science and Technology
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• v.4 no.4
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• pp.47-54
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• 1995

Sensory measurements are inevitably uncertain, and this may decrease the reliability of sensor feedback systems. In this paper we present a method to achieve reliable measurements using multiple sensors. Assuming sensors with unknown characteristics in dynamic surroundings, readings from the sensors are clustered and fused with the estimated degrees of credit. In the experiment performed with logical sensors the technique proposed is employed to adaptively estimate the measurand under the circumstances where an existing probabilistic technique is difficult to be applied. The technique proposed may be useful for automatic systems working in unstructured environments - for example, sensory robots employed for intelligent manipulation.

• 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 Korean Association for Spatial Structures
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• v.15 no.1
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• pp.75-84
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• 2015

This paper presents the dimensionless wall distance, y+ effect on SST turbulent model for wind turbine blade. The National Renewable Energy Laboratory (NREL) Phase VI wind turbine was used for the study, which the wind tunnel and structural test data has publicly available. The near wall treatment and turbulent characteristics have important role for proper CFD simulation. Most of the CFD development in this area is focused on advanced turbulence model closures including second moment closure models, and so called Low-Reynolds (low-Re) number and two-layer turbulence models. However, in many cases CFD aerodynamic predictions based on these standard models still show a large degree of uncertainty, which can be attributed to the use of the $\epsilon$-equation as the turbulence scale equation and the associated limitations of the near wall treatment. The present paper demonstrates the y+ definition effect on SST (Shear Stress Transport) turbulent model with advanced automatic near wall treatment model and Gamma theta transitional model for transition from lamina to turbulent flow using commercial ANSYS-CFX. In all cases the SST model shows to be superior, as it gives more accurate predictions and is less sensitive to grid variations.