• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.45-48
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• 2006

The system that can generate biological brain information processing mechanism more precisely may have several abilities such as exact cognition, situation decision, learning and inference, and output decision. In this paper, to implement high level information processing and thinking ability in a complex system, the information processing layer based on the biological brain is introduced. The biological brain information processing mechanism, which is analyzed in this paper, provides fundamental information about intelligent engineering system, and the design of the layer that can mimic the functions of a brain through engineering definitions can efficiently introduce an intelligent information processing method having a consistent flow in various engineering systems. The applications proposed in this paper are expected to take several roles as a unified model that generates information process in various areas, such as engineering and medical field, with a dream of implementing humanoid artificial intelligent system.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.10 no.1
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• pp.49-60
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• 2005

Existing CAD systems have configured geometry data and it is necessary to extend the configured geometry into a knowledge-based system. An intelligent CAD system emerged to provide such a knowledge-based system. However the intelligent CAD system has a limited product model to represent various knowledge models. This paper presents a model, called extended intelligent CAD model, which can extend the product model of the intelligent CAD system into further detailed knowledge model. The extended intelligent CAD model includes a whole design process knowledge and an efficiency of the model has been verified via a knowledge based wiper design system. The model can improve the functionality and efficiency of the existing CAD systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.351-351
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• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require an application of intelligent control system for a high rate heat efficiency and the efficiency of these systems is depended on the control methods it is important for operator to understand control system of these systems and intelligent control technologies. In order to properly apply control equipment and intelligent technology to these process control systems, it is necessary to understand fuzzy, neural network, genetics, and immune as well as the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, since PID controllers are used in these systems it is difficult far engineer to understand both the complex dynamics and the intelligent control method. In this paper, we design an effective experimental system for the intelligent control education and analyze its characteristics through experimental system and each intelligent method to study how they can learn intelligent control system by experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.221-224
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• 2005

This paper proposes the system model that is more efficient and active than formal home automation system and it can conquer the limits of formal one using intelligent mobile robot. This system uses specialized intelligent mobile robot for home environment and the robot moves around home instead of human. We call the system model to HAuPIRS (Home Automation system using PDA based Intelligent Robot System). HAuPIRS control architecture is composed three parts and each part is User Level, Cognitive Level, Executive Level. It is easy to use system and possible to extend the home apparatusfrom new technology. We made the PBMoRo System (PDA Based Mobile Robot System) based on HAuPIRS architecture and verified the efficiency of the system model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.200-208
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• 2014

This paper presents the control of an inverted pendulum system using intelligent algorithms, such as fuzzy logic and neural networks, for advanced control education. The swing up balancing control of the inverted pendulum system was performed using fuzzy logic. Because the switching time from swing to standing motion is important for successful balancing, the fuzzy control method was employed to regulate the energy associated with the angular velocity required for the pendulum to be in an upright position. When the inverted pendulum arrived within a range of angles found experimentally, the control was switched from fuzzy to proportional-integral-derivative control to balance the inverted pendulum. When the pendulum was balancing, a joystick was used to command the desired position for the pendulum to follow. Experimental results demonstrated the performance of the two intelligent control methods.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.309-314
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• 2009

This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education. Control purpose is to satisfy balancing angle and desired trajectory tracking performance. The adaptive neuro-fuzzy controller has the Takagi-Sugeno(T-S) fuzzy structure. Back-propagation algorithm is used for updating weights in the fuzzy control. Control performances of the inverted pendulum system by PID control method and the adaptive neuro-fuzzy control method are compared. Control hardware of a DSP 2812 board is used to achieve the real-time control performance. Experimental studies are conducted to show successful control performances of the inverted pendulum system by the adaptive neuro-fuzzy control method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.100-104
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• 2008

In this paper, intelligent filtering methodology for masterarm translation signal is proposed. Fidelity and stability are contradicting factors in teleoperation. Human hand trembling filtering is one of the problems in telemanipulation field. During every operation the hand has a certain vibration that can affect the quality of teleoperation, especially in carrying FPD (Flat Panel for Display), nanomanipuation and other precise tasks. It is very important to study the kinesthetic perception of the human and to optimize the teleoperation system accordingly. To cancel out the influence of human's hand vibration the signal from the masterarm should be filtered. One of the feasible solutions is to use an intelligent filter based on fuzzy logic, which is a very flexible instrument. Applying intelligent filtering methodology, we can use some heuristic methods to solve the filtering problem.