• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.503-512
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• 2006

Recently, intelligent agents are demanded increasingly automated techniques for animation according to interaction with user or environment of the user. In this paper, we have studied a generic framework for intelligent agents based on emotions. Intelligent agents are designed to infer emotions from diverse personalities, situations, user behaviors and to express them. We research into the technique and the case study for intelligent agents based on emotions supposing autonomous and interactive animation.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.409-413
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• 2001

This paper presents a comprehensive study result on reducing commutation torque ripples generated in brushless dc motor drives with only a single dc-link current sensor provided. In brushless dc motor drives with only a single current sensor, the commutation torque ripple suppression that is practically effective in low speed as well as high speed regions has not been reported. A proposed commutation compensation technique based on deadbeat dc-link current controller takes a closed loop control scheme and a parameter insensitive property. The proposed control method is verified through simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.378-384
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• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.139-145
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• 2002

In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.443-448
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• 1998

As the strip caster system that produces a regular steel plate can be considered as a complicate nonlinear multi-variable system, it is not easy to obtain an effective control system. One way to overcome the difficulties is to apply the intelligent neuro-fuzzy fusion approach in developing the control scheme. The neuro-fuzzy control scheme possesses several distinct advantages, including the fact that it doesn't need the exact mathematical modeling of controlled plant and can provided some robustness in the control scheme. In this paper, an intelligent neuro-fuzzy for the stripe caster system will be proposed. The effectiveness of the proposed scheme will be demonstrated by computer simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.129-132
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• 2003

This paper proposes a novel and efficient intelligent digital redesign technique for a Takagi-Sugeno (TS) fuzzy system. The term of intelligent digital redesign involves converting an existing analog fuzzy-model-based controller into an equivalent digital counterpart in the sense of state matching. In this paper, we suggest the discretization method based on the dual-rate sampling approximation is first proposed, and then attempt to globally match the states of the overall closed-loop TS fuzzy system with the pre-designed analog fuzzy-model-based controller and those with the digitally redesigned fuzzy-model-based controller. To show the feasibility and the effectiveness of the proposed method, a computer simulation is provided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• 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 the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.102-107
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• 2011

In this paper, pole-changing induction motor has been studied. To control the speed of the induction motor, many various methods can be used. Compared to the other speed control method, pole changing method is simple, cost effective, and reliable. From this research, pole changing induction motor with 2 and 4 pole windings are analyzed and designed, of which rated torque is about 2Nm. A real induction motor is also fabricated and some experiment has been performed showing that the analysis and experiment results are similar.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.83-88
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• 2001

To get the items that a buyer wants in Internet auction. he must search for the items through several auction sites. When the bidding starts, he(the buyer) needs to connect to these auction sites frequently so that he can monitor the bid stats and re-bid. A reserve-price auction reduces the number of connections, but this limits the user's bidding strategy. Another problem is equity between the buyer and the seller. Both the buyer and the seller should profit together within proper limits. In this paper, we propose an auction agent system using a collaborative mobile agent and a brokering mechanism called MoCAAS (Mobile Collaborative Auction Agent System), which mediates between the buyer and the seller and executes bidding asynchronously and autonomously. This reduces connection costs. offers more intelligent bidding and solves the equity problem.