• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.73-76
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• 2005

The advanced information and communication technology gives vehicles another role of the third digital space, merging a physical space with a virtual space in a ubiquitous society. In the ubiquitous environment, the vehicle becomes a sensor node, which has a computing and communication capability in the digital space of wired and wireless network. An intelligent vehicle information system with a remote control and diagnosis is one of the future vehicle systems that we can expect in the ubiquitous environment. However, for the intelligent vehicle system, many issues such as vehicle mobility, in-vehicle communication, service platform and network convergence should be resolved. In this paper, an in-vehicle gateway is presented for an intelligent vehicle information system to make an access to heterogeneous networks. It gives an access to the server systems on the internet via CDMA-based hierarchical module architecture. Some experiments was made to find out how long it takes to communicate between a vehicle's intelligent information system and an external server in the various environment. The results show that the average response time amounts to 776ms at fixec place, 707ms at rural area and 910ms at urban area.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1729-1734
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• 2005

The use of gantry crane systems for transporting payload is very common in industrial application. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. To overcome this problem, this paper describes development of an intelligent gantry crane system based on the mechatronic design. A lab-scale gantry crane is designed and then its intelligent controllers are developed. Fuzzy logic controllers are adopted, designed and implemented for controlling payload position as well as the swing angle of the gantry crane. The performance of the intelligent gantry crane system is evaluated on a hardware-in-the-loop simulation (HILS) environment. Moreover robustness of the proposed system is also evaluated. The result shows that the intelligent gantry crane system designed based on the mechatronic design approach has better performance compared with the automatic gantry crane system controlled by classical PID controllers. Moreover simulation result shows that the intelligent gantry crane system is more robust to parameter variation than the automatic gantry crane system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.68-74
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• 2008

In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.242-248
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• 2007

In this paper, we implement the internet-based remote control system for intelligent robot. For remote control of the robot, it uses the socket communication of the TCP/IP. It consists of the user interface and the robot control interface. Robot control interface transmits the navigation and environmental informations of the robot into the user interface. In order to transmit the large environmental images, a JPEG compression algorithm is used. User interface displays the navigation status of the robot and transmits the navigation order into the robot control interface. Also, we propose the design method of the fuzzy controller using navigation data acquired by expert's knowledge or experience. To do this, we use virus-evolutionary genetic algorithm(VEGA). Finally, we have shown the proposed system can be operated through the real world experimentations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.21-31
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• 1996

An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.181-186
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• 2005

Because of advanced control technology, Shop floor control system of various kinds of equipment and machinery need a web based remote monitoring to control process efficiently. This paper presents the development of Operation Control System. Operation Control System(OCS) is based on intelligent web monitoring, so that OCS is improved the working condition for the line of heat treatment process and the product's quality. The developed OCS is consisted of Atmega128(MCU) based on embedded system, running the data logging of the line of heat treatment process. Web monitoring system is based on CS8900 ethernet controller and TCP/IP for remote monitoring responsibility between a server and clients and controlling the progress of entire system. The developed OCS is implemented on the line of heat treatment process and shows the improvement of environment condition, product's quality and efficiency of process line.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.146-150
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• 2009

An Intelligent active roll angle controller design algorithm is discussed. The detailed mathematical formulation and analysis are discussed, and then modeling and design method for active roll angle controller are presented. This paper proposes a design method based upon intelligent robust controller design algorithm to control actively roll angle for improving cornering performance problems. The intelligent robust controller is designed for steady speed driving vehicle system model with representation of steering angle and yaw angular velocity parameters for cornering stability. And the detailed formulation and analysis for the objective vehicle system are investigated.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2653-2655
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• 1999

A technique to suppress the low frequency ripple voltage of the DC output voltage in three-phase buck diode rectifiers is presented. A pulse frequency modulation method is employed to regulate the output voltage of the rectifier and guarantee zero-current switching of the switch over the wide operating range. The pulse frequency control method used in this paper shows generally good performance such as low THD of the input line current and unity power factor. In addition, the pulse frequency method can be effectively used to suppress the low frequency voltage ripple appeared in the dc output voltage. The proposed technique illustrates its validity and effectiveness through the respective simulations and experiments.

• Journal of Drive and Control
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• v.20 no.4
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.