• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.123-126
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• 1995

Characteristics of control system design using Universal Learning Network (U.L.N.) are that a system to be controlled and a controller are both constructed by U.L.N. and that the controller is best tuned through learning. U.L.N has the same generalization ability as N.N.. So the controller constructed by U.L.N. is able to control the system in a favorable way under the condition different from the condition of the control system in learning stage. But stability can not be realized sufficiently. In this paper, we propose a robust control method using U.L.N. and second order derivatives of U.L.N.. The proposed method can realize better performance and robustness than the commonly used Neural Network. Robust control considered here is defined as follows. Even though initial values of node outputs change from those in learning, the control system is able to reduce its influence to other node outputs and can control the system in a preferable way as in the case of no variation. In order to realize such robust control, a new term concerning the variation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivatives of criterion function with respect to the parameters. Finally it is shown that the controller constricted by the proposed method works in an effective way through a simulation study of a nonlinear crane system.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.269-277
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• 2008

This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

• English Language & Literature Teaching
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• v.8 no.1
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• pp.39-53
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• 2002

Recently much research has investigated the role of attention in L2 learning, comparing the effects of explicit learning with those of implicit learning. With this background the research aims at examining the effects explicit focus on form has on L2 learning based on the acquisition of the English article system. The participants were 70 Korean college students who enrolled in English Composition classes. The experimental group received explicit focus on form including grammatical explanation, input enhancement, output practice, and negative evidence (corrective feedback) for two weeks, while the control group was exposed to sufficient input and negative evidence. Completion tasks were administered at the beginning and the end of the semester. In addition, errors in the use of English articles were analysed on their compositions both before and after the different treatments. The analyses of the results show that the explicit focus on form group improved significantly more than the control group, particularly for the definite article 'the', and some changes occurred in the distribution of article errors. These findings suggest that explicit teaching plays a more contributory role than implicit teaching in acquiring L2 knowledge in classroom-based L2 learning.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.95-98
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• 1996

Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated nodes and multi-branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed by ordinary first order difference equations with one sampling time delay. It has been already reported that learning algorithm of parameter variables in U.L.N. by forward and backward propagation is useful for modeling, managing and controlling of the large scale complicated systems such as industrial plants, economic, social and life phenomena. But, in the previous learning algorithm of U.L.N., time delays between the nodes were fixed, in other words, criterion function of U.L.N. was improved by adjusting only parameter variables. In this paper, a new learning algorithm is proposed, where not only parameter variables but also time delays between the nodes can be adjusted. Because time delays are integral numbers, adjustment of time delays can be carried out by a kind of random search procedure which executes intensified and diversified search in a single framework.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.111-114
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• 1996

This paper proposes a robust control method using Universal Learning Network(U.L.N.) and second order derivatives of U.L.N.. Robust control considered here is defined as follows. Even if external input (equal to reference input in this paper) to the system at control stage changes awfully from that at learning stage, the system can be controlled so as to maintain a good performance. In order to realize such a robust control, a new term concerning the perturbation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivative of the criterion function with respect to the parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.248-255
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• 2000

Whereas the linear PID controller is widely used for control of industrial servo systems a high precision positioning system is not easy to control only with the PID controller due to uncertain nonlinear dynamics such as friction backlash etc. As a viable means to overcome the difficulty a learning control scheme is proposed in this paper that is simple and straightforward to implement. The proposed learning controller takes full advantage of current feedback capability of the inner-loop of the control system in that electrical motor dynamics as the well as mechanical part of X-Y positioning system is included in the learning control scheme, The experimental results are given to demonstrate its feasibility and effectiveness in terms of convergence precision of tracking and robustness in comparison with the conventional control method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1182-1185
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• 1996

The objective of this paper is to control a nonlinear dynamical systems based on Self-Organized Distributed Networks (SODN). The learning with the SODN is fast and precise. Such properties are caused from the local learning mechanism Each local network learns only data in a subregion. Methods for indirect adaptive control of nonlinear systems using the SODN is presented. Through extensive simulation, the SODN is shown to be effective for adaptive control of nonlinear dynamic systems.

• The Journal of Korean Medicine
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• v.21 no.2
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• pp.25-36
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• 2000

Objectives : This study demonstrates the effects of Daejo-hwan on learning and memory impairment induced by L-NAME (75 mg/kg) treatment and on cerebral ischemic damage induced by middle cerebral artery (MCA) occlusion in rats. Methods : Daejo-hwan emulsion (73.3 mg/100 g/l ml) was administered to rats along a timed study schedule. The Moms water maze was used for learning and memory test of the rats. The MCA was occluded by using the intraluminal thread method. The brain slices were stained by 2 % triphenyl tetrazolium chloride (TTC) and 1 % cresyl violet solution. Infarct size, neuron cell number and size in penumbra was measured by using computer image analysis system. Results : 1. The escape latency of the Daejo-hwan treated group decreased significantly with respect to the control group. 2.The memory score of the Daejo-hwan treated group showed increase tendency, And the swimming distance was not different between the normal, the control, and the Daejo-hwan treated group. 3. The infarct size of the Daejo-hwan treated group decreased significantly with respect to the control group. 4. The total infarct volume of the Daejo-hwan treated group showed decrease tendency. And the brain edema index of the Daejo-hwan treated group decreased significantly with respect to the control group. 5. The neuron cell number and cell size in penumbra of the Daejo-hwan treated group increased significantly with respect to the control group. Conclusions : According to the above results, it is supposed that Daejo-hwan is clinically applicable to the vascular dementia.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.4
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• pp.351-357
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• 2003

An easy learning elevator originated is opened to compare the existed teaming equipment, and it had a high studied efficiency that the sequence control circuit can open and close with the wire. The structure of equipment to be controlled from the first floor to the fifth floors is demostrated by the constructive apparatus with the lamps to express the function of the open-close of the door according to the cage moving with a mechanical actuation of the forward reverse breaker and the motor of load, and the mechanical actuation of hand-operation control components of push-button S/W and L/S and relay etc. These components let connect each other in order to control of the elevator function with the auto program and the designed sequence control circuit. Consequently the cage could go and come till 1∼5 steps with an auto program of the elevator and the sequence control circuit. The sequence control circuit is controlled by the step of forward and reverse to follow as that the sensor function of L/S1 ∼ L/S5 let posit with the control switchs of S/W1 ∼ S/W5 of PLC testing panel and switchs of S/W1 ∼ S/W5 installed on the transparent acryl plate of the frame. In here, improved apparatus is the hand-auto operation combined learning equipment to study the principle and technique of the originate sequence control circuit and the auto program of PLC.

• English Language & Literature Teaching
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• v.16 no.4
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• pp.239-265
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• 2010

This study investigates the effects of corpus-based vocabulary tasks on the acquisition of English vocabulary in an attempt to explore the influence of corpus use on EFL pedagogy. For this to be realized, a total of 40 Korean high school students participated in the study over a 4-week period. An experimental group used a set of corpus-based tasks for vocabulary learning, whereas a control group carried out a traditional task (i.e., the L1-L2 translation) for vocabulary learning. To assess learning gains, the students were asked to complete the pre- and post-treatment tests measuring the word form, meaning, and use aspects of target lexical items. Results of the study indicate that in the experimental group the corpus-based vocabulary tasks were beneficial for the learning of word forms and use. In particular, corpus-based benefits were greatest in the low-proficiency EFL learners' collocational aspects of vocabulary use. On the other hand, in the control group, the traditional vocabulary tasks benefited the meaning aspects of target vocabulary items the most. In addition, survey results revealed that most students were positive about the corpus-based learning experience although some expressed reservations about the heavy cognitive load and the time-consuming nature of the analysis of corpus data primarily due to learners' lack of language proficiency.