• Journal of the Society of Naval Architects of Korea
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• v.48 no.1
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• pp.15-22
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• 2011

In this paper, cavitation patterns of model tests were compared with those of full-scale measurement for a propeller of crude oil carrier which was suffered from erosions on suction side of blade tip region. Cavitation tests were performed at design and ballast draft using model and full scale nominal wakes. A model ship and wire mesh method was used for the simulation of wake patterns of model nominal wakes. For the prediction of full-scale wake patterns, a RANS solver(Fluent 6.3) was used and wire mesh method was used for the simulation of the full scale wakes. Comparison results show that cavitation patterns using predicted full-scale wake patterns are closer to cavitation patterns of full-scale measurement at ballast draft condition. Also, cloud cavitations were observed on the position of eroded area at both full-scale measurement and cavitation tests using simulated full-scale wake patterns.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.60-67
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• 1990

This paper proposes a model-based fault detection method for linear/nonlinear system having modelling errors, nonlinearities and measurement noise. The system model is represented by the unified operator [5] in order to apply to both the continuous-time and discrete-time problems. The fault detection method suggested here accounts for the effects of noise, model mismatch and nonlinearities. Modelling errors are depicted by additive forms and the nominal model denominator is fixed via prior experiments in order to quantify the nucertainty bound on the parameter estima-tion. The least square method is used to estimate the numerator parameters of the nominal model. performance than traditional methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1036-1041
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• 2008

Periodic disturbance is practically occurred in several engineering applications, especially in data storage systems. However, recently addressed controls for such problem were mostly dealt with its deterministic nature, which is rarely practical in real-time implementation. We present an adaptive control approach for DC motor systems with periodic stochastic disturbance whose frequency and magnitude are both random variables. We establish adaptive state feedback control which is linearly composed of nominal and corrective control parameter matrices. The former is derived from a nominal system model voiding disturbance and the latter is constructed from a disturbed system model by using Lyapunov stability theory. We carry out computer simulation to evaluate the proposed control methodology and compare to the recently addressed control method to demonstrate its superiority.

• Journal of Power System Engineering
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• v.17 no.3
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• pp.82-88
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• 2013

For commercialized servo drives of the motion stage to include embedded controller, external terminal is provided for tracking command and encoder output, but internal terminal is not for control input. Thus, it is difficult to combine out signal of embedded controller with that of external compensator such as disturbance observer. In this study, for precise tracking control of motion stage without hardware change of the servo drive, tacking control system is composed of an inner loop of servo drive and an outer loop of disturbance observer. Then, the control system is designed so that the output response of actual plant corresponds with nominal model's in transient state as well as in steady state. Finally, the experiment results show that the designed control system is effective to reconcile actual plant behavior with nominal model under nonlinear friction and parameter perturbation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.543-550
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• 2002

This work is concerned with the estimation of output derivatives and their use for the design of robust controller for linear systems with systems uncertainties due to modeling errors and disturbance. It is assumed that a nominal transfer function model and Quantitative bounds for system uncertainties are known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted trough restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Controller) Type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.

• Journal of Ocean Engineering and Technology
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• v.10 no.3
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• pp.153-161
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• 1996

This paper presents a design method of dynamic positioning control system for floating platform with rotatable and retractable thruster using $H_{\infty}$ control technique. The norm band of uncertainty is captured by multiplicative perturbation between nominal model and reduced order model. A controller robust to the uncertainty is designed applying $H_{\infty}$ synthesis. The control law satisfying robust stabillity and nominal performance condition is determined through the mixed sensitivity approach. The evaluation for the resultant controller obtained by $H_{\infty}$ synthesis is done through simulations of the closed loop system. The results of $H_{\infty}$ synthesis are compared to those of the traditional LQ synthesis method.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.264-269
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• 2014

We consider transmission over body area networks. Due to the difficulty in assessing an accurate statistical model valid for multiple scenarios, we advocate a system design technique favoring robustness. Our approach, which is based on results in [12] and generalizes them, examines the variation of a performance metric when the nominal statistical distribution of fading is replaced by the worst distribution within a given Kullback-Leibler divergence from it. The sensitivity of the performance metric to the divergence from the nominal distribution can be used as an indication of the design robustness. This concept is applied by evaluating the error probability of binary uncoded modulation and the outage probability-the first parameter is useful to assess system performance with no error-control coding, while the second reflects the performance when a near-optimal code is used. The usefulness of channel coding can be assessed by comparing its robustness with that of uncoded transmission.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2257-2264
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• 1994

A method to evaluate the position performance for a stochastically defined planar robot manipulator is presented. Performance is defined as the operational reliability based upon the positional errors of the manipulator tip. An analytical method is developed and applied to a two-link robot manipulator through forward kinematics. This study includes uncertainties in the link length, pin center location and radial clearance. By virtue of the effective link length model, only the nominal manipulator model and statistical information on the uncertainties are required. The results from the analytical method is compared to those from the Monte Carlo simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.647-651
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• 1992

This paper presents a model-based control scheme for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload. The scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighborhood of the trajectory. Then a discrete-time PID regulator is designed based on the linearized dynamic model and Linear Quadratic(LQ) method, which generates the variational control that regulates perturbations in the vicinity of the desired trajectory.

• Journal of Mechanical Science and Technology
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• v.20 no.5
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• pp.591-601
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• 2006

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.