• CDE review
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• v.11 no.2
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• pp.15-22
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• 2005

Presented in the paper is an approach to developing an intelligent mold shop as a means to overcome the difficulties faced by mold-makers due to skill shortages and increased global competition. A machine shop where as much as of the human skills are replaced by a set of intelligent systems is called an intelligent machine shop, and an intelligent mold-making machine shop is called an intelligent mold shop(MS). By analyzing the contents of operator's skill. three intelligent S/W stations have been designed: Technical Data Processing(TDP) Station, Loading Schedule Station, and Real-time Monitoring Station. A detailed architecture of the TDP station is described, and measures of effectiveness of IMS are elaborated.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.393-397
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• 2001

This paper addresses an Intelligent Agent-based Open Architecture Cell Controller for Intelligent Manufacturing System(IMS). With an Intelligent Agent approach, the IMS will be a independent, autonomous, distributed system and achieve a adaptability to change of manufacturing environment. As the development methodology of Open Architecture Cell Controller, an object-oriented modeling technique is employed for building models associated with IMS operation, such as resource model, product model, and control model. Intelligent Agent-based Open Architecture Cell Controller consists of two kinds of dependant agents, that are the active agent and the coordinator agent. The Active agent is contributed to control components of IMS in real-time. The coordinator agent has great role in scheduling and planning of IMS. It communicates with other active agents to get information about status on system and generates the next optimal task through the making-decision logic and dispatch it to other active agent.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.113-118
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• 2001

In this paper, we develop an optimal intelligent digital redesign method for a class of fuzzy-model-based controllers, effective for stabilization of continuous-time complex nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to extend the results of the classical digital redesign technique to complex nonlinear systems. Unlike the conventional intelligent digital redesign technique reported in the literature, the proposed method utilized the recently developed LMI optimization technique to obtain a digitally redesigned fuzzy-model-based controller. Precisely speaking, the intelligent digital redesign problem is converted to an equivalent optimization problem, and the LMI optimization method is used to find the digitally redesigned fuzzy-model-based controller. A numerical example is provided to evaluate the feasibility of the proposed approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.246-252
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• 2005

Intelligent Space is a space where many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents, which provide human with services. To realize this, human and mobile robots have to approach each other as much as possible. Moreover, it is necessary for them to perform interactions naturally. It is desirable for a mobile robot to carry out human affinitive movement. In this research, a mobile robot is controlled by the Intelligent Space through its resources. The mobile robot is controlled to follow walking human as stably and precisely as possible. In order to follow a human, control law is derived from the assumption that a human and a mobile robot are connected with a virtual spring model. Input velocity to a mobile robot is generated on the basis of the elastic force from the virtual spring in this model. And its performance is verified by the computer simulation and the experiment.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.393-394
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• 2007

Speaker Recognition for the Intelligent Service Robot is implemented in this paper. For this purpose, we perform speaker recognition based on Gaussian Mixture Model(GMM) and use robot platform called WEVER, which is a Ubiquitous Robotic Companion(URC) intelligent service robot developed at Intelligent Robot Research Division in ETRI. The experimental results reveals that the approach presented in this paper yields a good identification (89.00%) performance within 2 meter distance.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• The Journal of Information Systems
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• v.10 no.2
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• pp.5-32
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• 2001

The main goal of this research is at the development of a bundle product suggestion sub-system of an internet shopping mall for fishery products, which can reduce the search cost of user. To achieve the goal, we first study tie key factors of successful direct commerce for fishery products, and second, we design a bundle product suggestion module and its sub-module. For this, we identify the objectives of system, and write out the necessary functions of the system and models(process model, data model, dynamic model) through the analysis of user requirements. Based on the functions and models, we design user interfaces, database, processes, and knowledge base. In designing knowledge base and inferencing strategy, we consider two intelligent agent approach(optimal algorithms, heuristic rules) and suggest one more approach(case-based reasoning). The intelligent agent can be used in enhancing the suggestion of multiple fishery product simultaneously. The system analysis and design documents presented as the research results can be used to provide good guidelines to the companies who consider developing an production suggestion agents.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.292-297
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• 2013

Nowadays, a strategy of the self-optimizing machining process is an imperative approach to improve the product quality and increase productivity of manufacturing systems. This paper presents a concept of self-optimizing forming system that allows the forming system automatically to adjust the forming parameters online for guarantee the product quality and avoiding the machine stop. An intelligent monitoring system that has the functions of observation, evaluation and diagnostic is developed to evaluate the pully quality during forming process. Any abnormal variation of forming machining parameters could be detected and adjusted by an intelligent control system aiming to maintain the machining stability and the desired product quality. This approach is being practiced on the pully forming machine for evaluating the efficiency of the proposed strategy.