• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.38.5-38
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• 2001

In this paper, we propose new digital optimal control approach for controlling continuous-time nonlinear chaotic systems, which show very complex behavior and cannot be easily controlled by conventional control methods. Most real systems are represented as continuous-time system, whereas some control methods should be implemented under the condition of computer-based platforms, which are discrete-time systems. To achieve the control objective for chaotic systems successfully, the sampled-data controller, which considers the inter-sample behavior of the continuous-time systems effectively, should be needed. The proposed optimal controller is designed based on the linearized estimation model of chaotic systems. By the computer simulation, we show the control ...

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.458-460
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• 2009

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1232-1240
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• 2018

This paper aims at designing an intelligent controller, based on control Lyapunov Function strategy integrated with fabricating discrete model of Buck and Boost converters and analyzing energy changes during the DC/DC progress to realize tracing reference current on Buck and Boost converters. In addition, practical stability phenomenon research and transient performance analysis has been proposed to give an insight to the influence of controller parameters in achieving an enhanced output performance and how the time of sample period affect the error of practical stability will be illustrated. The novelty of this controller in comparison to other schemes lies in the improved performance of practical stability.

• Journal of Engineering Education Research
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• v.12 no.2
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• pp.89-95
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• 2009

This thesis investigated way of employment, education course of a training school of Programmable Logic Controller a Field. I inquired into a demand of an engineer and a necessary level of professional education. As a result, I have a purpose in what offer the information that cared for a beginning to work elevation and education training and boat development of a student more than. Faced a human power demand in an education demand and a field rehearsal student demand and analyzed it. The sample extraction used industrial classification, work of scale, Assignment sample extraction way (quota sampling). All data called at a silver phone and the investigated, The data parser analyzed the statistics that used Microsoft Excel.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.149-154
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• 2006

In this paper, for auto temperature-controlled, we developed a system that an adaptive fuzzy controller using fuzzy control rule base, fuzzy variable and fuzzy inference can get same results as an expert of temperature -controlled gas furnace system by experience and obtained a good result by experiment. It's results showed that temperature error is less than ${\pm}2^{\circ}C$ and widely used in the area of industrial fields. For measurement of error rate of sintered ceramic products between the manual system and the proposed system, we tested two times sample A and B respectively. We verified the improvement of error rate was mean 50.5% and 48.4% for each sample A and B. Through the experiments, we confirmed that it has very superior performance compared with the conventional gas furnace system by manual.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.869-879
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• 1995

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of learning control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. In the previous paper, I had studied the use of such controllers in a decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short. In this paper, we present two examples. The first illustrates the effect of coupling between subsystems in the system dynamics, and the second studies the application of decentralized learning control to robot problems. The latter example illustrates the application of decentralized learning control to nonlinear systems, and also studies the effect of the coupling between subsystems introduced in the input matrix by the discretization of the system equations. The conclusion is that for sufficiently small learning gain, and sufficiently small sample time, the simple learning control law based on integral control applied to each robot axis will produce zero tracking error in spite o the dynamic coupling in the robot equations. Of course, the results of this paper have much more general application than just to the robotics tracking problem. Convergence in decentralized systems is seen to depend only on the input and output matrices, provided the sample time is suffiently small.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.323-329
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• 2020

This paper presents a control algorithm for a wearable walking aid robot for subjects with paraplegia after stroke. After a stroke, a slow, asymmetrical and unstable gait pattern is observed in a number of patients. In many cases, one leg can move in a relatively normal pattern, while the other leg is dysfunctional due to paralysis. We have adopted the so-called assist-as-needed control that encourages the patient to walk as much as possible while the robot assists as necessary to create the gait motion of the paralyzed leg. A virtual wall was implemented for the assist-as-needed control. A position based admittance controller was applied in the swing phase to follow human intentions for both the normal and paralyzed legs. A position controller was applied in the stance phase for both legs. A power controller was applied to obtain stable performance in that the output power of the system was delimited during the sample interval. In order to verify the proposed control algorithm, we performed a simulation with 1-DOF leg models. The preliminary results have shown that the control algorithm can follow human intentions during the swing phase by providing as much assistance as needed. In addition, the virtual wall effectively guided the paralyzed leg with stable force display.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.741-749
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• 2014

This paper proposes a machine vision module for PLCs (Programmable Logic Controllers). PLC is the industrial controller most widely used in factory automation system. However most of the machine vision systems are based on PC (Personal Computer). The machine vision system embedded in PLC is required to reduce the cost and improve the convenience of implementation. In this paper, we newly propose a machine vision module based on PLC. The image processing libraries are implemented and integrated with the PLC programming tool. In order to interface the libraries with ladder programming, the ladder instruction set was also designed for each vision library. By use of the developed system, PLC users can implement vision systems easily by ladder programming. The developed system was applied to sample inspection system to verify the performance. The experimental results show that the proposed system can reduce the cost of installing as well as increase the ease-of-implementation.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.139-145
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• 2006

A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.468-472
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• 2003

The lifting technique is a standard control procedure that is commonly applied to dual-rate systems, where a critical difficulty is that care must be taken so that the resulting equivalent system preserves the causality constraint between the control signal and the measured output. To overcome this difficulty, the most attractive result has been suggested by defining control time sequences as the union of sample and hold time sequences. However, the sacrifice of regular control period scheme results in some serious disadvantages; restrictions on the implementation to hardware and the corresponding inefficient control scheme. On the contrary, this paper proposes a novel dual-rate control technique, which redescribes the system as a control-rate-based system having regular control period and designs the controller, with no causality constraint, through Linear Matrix Inequality (LMI) formulation.