• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.363-366
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• 1990

In the indirect vector control method, the rotor resistance variation caused by operating temperature change is an undesirable nature. A new adaptation algorithm to compensate for the rotor resistance change based on the on-line estimation of field vector which requires the measurements of stator voltage and rotor speed is presented in this paper. Also minimum variance controller is presented for the adaptive control performance. This algorithm has been tested by simulating the induction machine using a digital computer and the results are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.247-264
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• 2008

This paper considers the integrated process control procedure for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. It is assumed that a special cause can change the process mean and the process variance. We derive expressions for the process deviation from target for a variety of different process parameter changes, and introduce a control chart, based on the generalized likelihood ratio, for detecting special causes. We also propose the integrated process control scheme bases on the future loss. The future loss denotes the cost that will be incurred in a process remaining interval from a true out-of-control signal.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.663-668
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• 1990

This paper deals with the application of a Generalized Predictive Control (CPC) to a Pressurized Water Reactor (P.W.R) Nuclear Power Plant. Generalized Predictive Control is a sort of Explicit Self-Tuning Control. Current self-tuning algorithms lack robustness to prior choices of either dead-time (input time delay of a plant) or model order. GPC is shown by simulation studies to be superior to accepted self-tuning techniques such as minimum variance and pole-placement from the viewpoint that it is robust to prior choices of dead-time or model order. In this paper a GPC controller is designed to control the P.W.R. nuclear power rlant with varying dead-time and through the designing procedure the designer is free from the constraint of knowing the exact dead-time. The controller is constructed based on the 2nd order linear model approximated in the vicinity of operating point. To ensure that this low-order model describes the complex real dynamics well enough for control purposes, model parameters are updated on-line with a Recursive Least Squares algorithm. Simulation results are successful and show the possibilities of the GPC control application to actual plants with varying or unknown dead-time.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.306-311
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• 1996

This paper discusses the maintenance of the water level of steam generators at its programmed value. The process, the water level of a steam generator, has the nonminimum phase property. So, it causes a reverse dynamics called a swell and shrink phenomenon. This phenomenon is severe in a low power condition below 15 %, in turn makes the start-up of the power plant too difficult. The control algorithm used here incorporates a pole-assignment scheme into the minimum variance strategy and we use a parallel adaptation algorithm for the parameter estimation, which is robust to noises. As a result, the total control system can keep the water level constant during full power by locating closed-loop poles appropriately, although the process has the characteristics of high complexity and nonlinearity. Also, the extra perturbation signals are added to the input signal such that the control system guarantee persistently exciting. In order to confirm the control performance of a proposed pole-assignment self-tuning controller we perform a computer simulation in full power range.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.283-292
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• 1996

Automatic guidance of farm tractors would improve productivity by reducing operator fatigue and increasing machine performance. To control tractors within $\pm$5cm of the desired path, fuzzy and adaptive steering controllers were developed to evaluate their characteristics and performance. Two input variables were position and yaw errors, and a steering command was fed to tractor model as controller output. Trapezoidal membership functions were used in the fuzzy controller, and a minimum-variance adaptive controller was implemented into the 2-DOF discrete-time input-output model. For unit-step and composite paths, a dynamic tractor simulator was used to test the controllers developed. The results showed that both controllers could control the tractor within $\pm$5cm error from the defined path and the position error of tractor by fuzzy controller was the bigger of the two. Through simulations, the output of self-tuning adaptive controller was relatively smooth, but the fuzzy controller was very sensitive by the change of gain and the shape of membership functions. Contrarily, modeling procedure of the fuzzy controller was simple, but the adaptive controller had very complex procedure of design and showed that control performance was affected greatly by the order of its model.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.357-365
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• 2010

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) noise process that is being adjusted using a minimum mean squared error adjustment. As a SPC procedure, we use a GLR chart for detecting special causes whose effects are the sustained shift or the sustained drift in the process mean, and the sustained shift in the process variance. For the design of the GLR chart, we derive expressions for the control limit which accurately satisfies the given in-control ARL.

• The korean journal of orthodontics
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• v.54 no.3
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• pp.153-159
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• 2024

Objective: This study aimed to assess the effects of commonly consumed hot drinks on the force decay of orthodontic elastomeric chains. Methods: This in vitro experimental study evaluated 375 pieces of elastomeric chains with six rings placed on a jig. Four rings were stretched by 23.5 mm corresponding to the approximate distance between the canine and the second premolar. Fifteen pieces served as reference samples at time zero, and 360 pieces were randomized into four groups: control, hot water, hot tea, and hot coffee. Each group was further divided into six subgroups (n = 15) according to the different exposure periods. The specimens in the experimental groups were exposed to the respective solutions at 65.5℃ four times per day for 90 seconds at 5-second intervals. The control group was exposed to artificial saliva at 37℃. The force decay of the samples was measured at 1, 2, 7, 14, 21, and 28 days using a universal testing machine. Data were analyzed using repeated-measures analysis of variance. Results: Maximum force decay occurred on day 1 in all groups. The minimum force was recorded in the control group, followed by the tea, coffee, and hot water groups on day 1. At the other time points, the minimum force was observed in the tea group, followed by the control, coffee, and hot water groups. Conclusions: Patients can consume hot drinks without concern about any adverse effect on force decay of the orthodontic elastomeric chains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.1009-1017
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• 1993

The Robust Adaptive Servo Controller in this paper has an error-corrected and robust structure which guarantees asymptotic regulation and tracking in the presence of bounded parameter perturbations. The adaptive mechanism tunes the controller parameters such that a quadratic performance index is minimized. Through the speed and position control of the DC servo model with computer simulations, the minimum variance controller parameters are robust with respect to finite parameter perturbation and bounded disturbance.