• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.259-272
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• 2022

The branch of electronics that uses an organic solar cell or conductive organic polymers in order to yield electricity from sunlight is called photovoltaic. Regarding this crucial issue, an artificial intelligence-based predictor is presented to investigate the vibrational behavior of the organic solar cell. In addition, the generalized differential quadrature method (GDQM) is utilized to extract the results. The validation examination is done to confirm the credibility of the results. Then, the deep neural network with fully connected layers (DNN-FCL) is trained by means of Adam optimization on the dataset whose members are the vibration response of the design-points. By determining the optimum values for the biases along with weights of DNN-FCL, one can predict the vibrational characteristics of any organic solar cell by knowing the properties defined as the inputs of the mentioned DNN. To assess the ability of the proposed artificial intelligence-based model in prediction of the vibrational response of the organic solar cell, the authors monitored the mean squared error in different steps of the training the DNN-FCL and they observed that the convergency of the results is excellent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.311-317
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• 2009

The traditional network anomaly detection systems execute the threshold-based detection without considering dynamic network environments, which causes false positive and limits an effective resource utilization. To overcome the drawbacks, we present the adaptive network anomaly detection model based on artificial immune system (AIS) in centralized network. AIS is inspired from human immune system that has learning, adaptation and memory. In our proposed model, the interaction between dendritic cell and T-cell of human immune system is adopted. We design the main components, such as central node and router node, and define functions of them. The central node analyzes the anomaly information received from the related router nodes, decides response policy and sends the policy to corresponding nodes. The router node consists of detector module and responder module. The detector module perceives the anomaly depending on learning data and the responder module settles the anomaly according to the policy received from central node. Finally we evaluate the possibility of the proposed detection model through simulation.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.699-702
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• 1991

A servo system requires faster and more accurate dynamic responses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, a Fuzzy controller with a series of membership functions, and various sampling periods and rules, was designed on the basis of Lyapunov stability theory and auto tuning methods of input scale factors. And also it was showed to have the excellent adaptive performances against internal-external disturbances and the usefulness of this controller from the results of simulations.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.421-424
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• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.249-253
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• 2004

This paper presents an implementation of position control system of Switched Reluctance Motor (SRM) using digital hysteresis controller. Although SRM possess several advantages including simple structure and high efficiency, the control drive system using power semiconductor device is required to drive this motor. The control drive system increases overall system cost. To overcome this problem and increase the application of SRM, it is needed to develope the servo drive system of SRM. So, the position control system of 1 Hp SRM is developed and evaluated by adaptive switching angle control. The position/speed response characteristics and voltage/current waveforms are presented to prove the capability of SRM for a servo drive application. Moreover, digital hysteresis current controller is developed and evaluated by experimental testing for the purpose of system developmental cost reduction.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.8-14
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• 2005

This paper is proposed hybrid artificial intelligent(HAI) controller for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on HAI controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the HAI controller is evaluated by analysis for various operating conditions. The results of analysis 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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• 2002.10a
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• pp.120.3-120
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• 2002

1. Introduction $\textbullet$ Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etc. Immune algorithm is the modeling of this system's response that has adaptation and reliableness when disturbance occur. $\textbullet$ In this paper, Immune algorithm is applied to the Steering Controller of AGV in container yard. $\textbullet$ And then the computer simulation result from the viewpoint of yaw rate and lateral displacement is analyzed and compared with result of conventional PID controller. 2. Dynamic Modeling of AGV $\textbullet$ Dynamic modeling has high degree of freedom. But, basic assumptions of this model are that the center of gravity(CG)...

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.137-143
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• 2002

This paper presents the In-process compensation to control cutter runout and improve the machined surface quality. Cutter runout compensation system consists of the micro-positioning servo system with piezoelectric actuator which is embeded in the sliding table to manipulate radial depth of cut in real-time. Cutting force feedback control was proposed in the angle domain based upon repetitive learning control strategy to eliminate chip load variation in end milling process. Micro-positioning control due to adaptive actuation force response improves the machined surface quality by compensation runout effect induced cutting force variation. This result will provide lots of information to build-up the preciswion machining technology.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.207-209
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• 1995

The PID controller is widely used due to its fast response and robustness. But its performance is not so good compared with modem controllers such as adaptive, robust, fuzzy, neural controller. Therefore, it is natural to replace PID controller by modem controllers. But, the problem is that modem controller can not be easily applied to the real time process. Hence, this paper proposes such a structure that PID controller and Self-Learning Fuzzy Controller(SLFC) are in parallel with each other. The parameter of SLFC will be updated by gradient descent method using neuro - identifier. The usefulness of this hybrid controller will be proved by simulation results.

• 연구논문집
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• s.30
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• pp.169-176
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• 2000

The Evolution of Workflow Managment consists of rhe automation of business procedures or "workflows" during which documents, information or tasks are passed from one participant to another in a way that is governed by rules or procedures. Workflow technologies have evolved from image management system, document management system, relational or object database systems, and electronic mail system. Workflow Management system has the benefits to improve better efficiency, process control,flexibility, business process. Automation of many business processes results in the elimination standdardizing working methods. Consistency in the processes leads to greater predictability in levels of response to customers and software control over processes enables their re-design in line with changing business needs, In this present study, we implement Electronic Approval System which is a kind of Workflow Management system using static and dynamic flow control information on the web environment.