• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.8-17
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• 2004

In this paper, we design an intelligent loaming management logics which provide personalized teaming considering adaptive learning content dement and content sequencing. We enhance the existing functional model including adaptive learning management functions. Also, we present a system architecture to implement the adaptive learning management system. We realize the adaptive teaming management system based on the SCORM run-time engine.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.5
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• pp.271-279
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• 2006

In this paper, a new speed sensorless control based on an adaptive sliding mode observer is proposed lot the interior permanent magnet synchronous motor(IPMSM) drives. With using voltage equation only, the adaptive sliding mode observer was investigated. Since the parameter of the dynamic equation such as machine inertia or viscosity friction coefficient are not well known and these values can be easily changed during normal operation, there are many restrictions in the actual implementation. The proposed adaptive sliding mode observer applied to overcome the problem caused by using the dynamic equation. Furthermore, the Lyapunov function is used to prove the system stability included speed estimate and speed control. The effectiveness of the proposed algorithm is confirmed by the experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.312-316
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• 2004

In this paper, it is presented an adaptive robust control system to implement real-time control of a robot manipulator. There are Quantitative or qualitative differences between a real robot manipulator and a robot modeling. In order to compensate these differences, uncertain factors are added to a robot modeling. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, etc. Also, uncertainty is often nonlinear and time-varying. In the proceeding work, we proposed a class of robust control of a robot manipulator and provided the stability analysis. In the work, we propose a class of adaptive robust control of robot manipulator with bound estimation. Through experiments, the proposed adaptive robust control scheme is proved to be an efficient control technique for real-time control of a robot system using DSP.

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.3
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• pp.35-41
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• 1981

In this paper, the application of model reference adaptive control theory to the D.C motor speed control using the microprocessor is studied. It is shown that with the use of an adaptive control algorithm the error between output of the motor and the reference model, which is approximated to first order, can be conve to zero. By computer simulation and the practical implementation with the microprocessor M 6800, can be concluded that the adaptive control system adapts well to the rapid change of the load and reference inputs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• Smart Structures and Systems
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• v.9 no.5
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• pp.411-426
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• 2012

Thin-walled adaptive structures render a large and important group of adaptive structures. Typical material system used for them is a composite laminate that includes piezoelectric material based sensors and actuators. The piezoelectric active elements are in the form of thin patches bonded onto or embedded into the structure. Among different types of patches, the paper considers those polarized in the thickness direction. The finite element method (FEM) imposed itself as an essential technical support for the needs of structural design. This paper gives a brief description of a developed shell type finite element for active/adaptive thin-walled structures and the element is, furthermore, used as a tool to consider the aspect of mesh distortion over the surface of actuators and sensors. The aspect is of significance for simulation of behavior of adaptive structures and implementation of control algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.6
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• pp.308-316
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• 1985

A new implementation of Block Adaptive filter in frequency domain is presented in this paper. Block digital filtering involves the calculation of a block or finite set of filter out put from a block of input values. A fast convergence algorithm of block adaptive filter is developed using Gordar theory and compared with the performance results of Satio algorithm and BLMS algorithm. Form the result we can be shown that the convergence state of given algorithm is not only faster than BLMS algorithm but also the resulting convergence error is less than the convergence error of Satio algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.114-118
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• 1996

This paper proposes a new technique to the design of adaptive control system using DSPs(TMS320C50) for Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved second stability analysis based on the indirect adaptive control theory. The proposed control scheme is simple in structure, fast in computation. an suitable for implementation of real-time control. Moreover, this scheme does not requre an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by exeperimental reults for a SCARA robot.

• 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.