• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.1
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• pp.1-6
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• 2014

In this paper, controller propose to prevent compressor surge and improve the transient response of the fuel flow control system of turbojet engine. Turbojet engine controller is designed by applying Artificial Neural Network PID control algorithm and make an inference by applying Levenberg-Marquartdt Error Back Propagation Algorithm. Artificial Neural Network inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbojet engine for UAV. High Gain Observer is used to estimate to compressor rotation speed of turbojet engine. Using MATLAB to perform computer simulations verified the performance of the proposed controller. Response characteristics pursuant to the gain were analyzed by simulation.

• Journal of KSNVE
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• v.6 no.5
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• pp.555-565
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• 1996

This paper is concerned with the theoretical and experimental study on the force control of a miniature robotic finger that grasps an object at three other positions with the fingertip. The artificial finger is a uniform flexible cantilever beam equipped with a distributed set of compact grasping force sensors. Control action is applied by a piezoceramic bimorph strip placed at the base of the finger. The mathematical model of the assembled electro- mechanical system is developed. The distributed sensors are described by a set of concentrated mass-spring system. The formulated equations of motion are then applied to a control problem in which the finger is commanded to grasp an object. The H$_{\infty}$-controller is introduced to drive the finger. The usefulness of the proposed control technique is verified by simulation and experiment..

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.898-906
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• 1999

A control structure is introduced for the purpose of rejecting periodic (or repetitive) disturbances on a tracking system. The objective of the proposed structure is to drive the output of the system to the reference input that will result in perfect following without any changing the inner configuration of the system. The structure includes an adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances, on the output of the system to be reduced. Since the control structure acquires the dynamics of the disturbance by on-line adaptation, it is possible to generate control signals that reject any slowly varying time-periodic disturbance provided that its amplitude is bounded. The artificial neural network is adopted as the adaptation block. The adaptation is done at an on-line process. For this , the real-time recurrent learning (RTRL) algoritnm is applied to the training of the artificial neural network.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.94-103
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• 1996

This paper is concerned with the theroretical and experimental study on the force control of a miniature robotic finger that grasps an object at three other positions with the fingertip. The artificial finger is uniform flexible cantilever beam equipped with a distributed set of compact grasping force secnsors. Control action is applied by a qiexoceramic bimorph strip placed at the base of the finger. The mathematical model of the assembled electro-mechanical system is developed. The distributed sensors are described by a set of concentrated mass-spring system. The formulated equations of motion are then applied to a control problem which the finger is commanded to grasp an object The PID-controller is introduced to drive the finger. The usefulness of the proposed control technique is verified by simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.201-206
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• 1996

This paper presents a new information processing machine which is called artificial brain(ABrain) and considers the structure of artificial neural networks constructed in a RICOH neurocomputer RN-2000 in the ABrain, in order to track given trajectories which are produced in a micro-computer or a moving light by hand in a recognition and tracking system.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.737-738
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• 2006

This paper is proposed hybrid artificial intelligent controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.19-23
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• 1996

A full automatic interpretation of awake electroencephalogram (EEG) had been developed by the authors and presented at the past KACCs in series. The automatic EEG interpretation consists of four main parts: quantitative EEG interpretation, EEG report making, preprocessing of EEG data and adaptable EEG interpretation. The automatic EEG interpretation reveals essentially the same findings as the electroencephalographer's (EEG's), and then would be applicable in clinical use as an assistant tool for EEGer. The method had been developed through collaboration works between the engineering field (Saga University) and the medical field (Kyoto University). This work can be understood as an artificial realization of human expert skill. The procedure for the artificial realization was summarized in a methodology for artificial realization of human skill which will be applicable in other fields of systems control.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.540-545
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• 2012

In this paper, we propose a fault diagnosis method using artificial neural network and SVM (Support Vector Machine) to detect and isolate faults in the nonlinear systems. The proposed algorithm consists of two main parts: fault detection through threshold testing using a artificial neural network and fault isolation by SVM fault classifier. In the proposed method a fault is detected when the errors between the actual system output and the artificial neural network nominal system output cross a predetermined threshold. Once a fault in the nonlinear system is detected the SVM fault classifier isolates the fault. The computer simulation results demonstrate the effectiveness of the proposed SVM and artificial neural network based fault diagnosis method.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.393-406
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• 2023

Smart structures are those structure that could adopt some behavior to prevent instability in their responses. The recognition of stability deterioration has been performed through rigid mathematical formulations in control theory and unpredicted results could not be addressed in control systems since they are able to only work under their predefined condition. On the other hand, incorporating all affecting parameters could result in high computational cost and delay time in the response of the systems. Artificial intelligence (AI) method has shown to be a promising methodology not only in the computer science by at everyday life and in engineering problems. In the present study, we exploit the capabilities of artificial intelligence method to obtain frequency response of a smart structure. In this regard, a comprehensive development of equations is presented using Hamilton' principle and first order shear deformation theory. The equations were solved by numerical methods and the results are used to train an artificial neural network (ANN). It is demonstrated that ANN modeling could provide accurate results in comparison to the numerical solutions and it take less time than numerical solution.

• The Journal of Korean Society for School & Community Health Education
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• v.9 no.2
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• pp.91-103
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• 2008

Objectives: This study was performed in order to evaluate the quality of health services provided to the adolescents at mobile health clinics and to improve the services for them, and to figure out knowledge level of adolescents on sex, birth control methods and artificial abortion, and the effect of the knowledge levels those items on sexual behavior. The data obtained will be utilized for sex health education program in the future. Methodology: A total of 2,021 adolescents who visited mobile sexual health clinics in Seoul, Inchon, Busan, Daejon, Cheonbuk, Kwangju and Daegu were surveyed in November 2007. The items surveyed were level of satisfaction about the services provided by mobile sexual health clinics, personal opinions and experience of artificial abortion, knowledge level about birth control, sexual experience and pregnancy. The above mentioned items were analyzed by general characteristics such as religion and geographical area. Results: The study subjects were generally satisfied with the services of mobile sexual health clinics. But they were not satisfied with the information about birth control methods provided by the clinics. The subjects who had better knowledge about sex were more satisfied with the services provided by the clinics. And the subjects who had knowledge about birth control methods but did not have birth control experience were also more satisfied with the services of clinics. The subjects who reported that artificial abortion should be allowed were also more satisfied with the services of the clinics. Experiences of sex, pregnancy, and artificial abortion were not correlated to satisfaction of the clinic services. Conclusions: The mobile sexual health clinics have to continues to provide sex health education and other sex related health services to adolescents. More practical information about birth control methods should be provided to the adolescents by the clinics based on the study results. Active preventive measures for unwanted pregnancy should be provided to the adolescents by the clinics.