• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.152-159
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• 1997

The asymptotic convergence of a coupled dynamic system, which is motivated from infinite dimensional adaptive systems, is investigated. The convergence analysis is formulated in abstract Banch spaces and is shown to applicable to a broad class of infinite dimensional systems including adaptive identification and adaptive control. Particularly it is shown that if a uniquely existing solution is p-th power integrable, then the solution converges to zero asymptotically. The persistence of excitation(PE) of a signal which arises in an infinite dimensional adaptive system is investigated. The PE property is not completely known yet for infinite dimensional adaptive systems, however it should be investigated in relation to spatial variable, boundary conditions as well as time variable.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.89-96
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• 2016

The performance of anti-submarine sonar detection is required to improve by the development of submarine noise reduction technology. because of the need of an anti-submarine detection ability, known for superior beamforming performance, adaptive beamforming algorithms have been considered as an alternative beamforming algorithm of a conventional beamforming algorithm. In order to achieve improved performance by applying an adaptive beamforming algorithm to the sonar system, the adaptive beamforming algorithm applicability of system must be verified, To do this, the performance index for the system applicability must be established. In this paper, a tracking initiation probability of the adaptive beamforming algorithm and the conventional beamforming algorithm was calculated and the performance of both techniques was quantified, a system applicability of the adaptive beamforming algorithm was reviewed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.236-241
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• 2007

This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.102-108
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• 2008

This paper presents robust and adaptive control method for complicated three dimensional crane systems with uncertain effect. We consider an overhead crane system in which a trolly located on its top is moved to x- and y-axis independently. We first approximate the complicated crane model through linearization approach to simply construct a PD control and then design an adaptive control system for compensating modeling error and control deviation which is feasibly occurred due to system perturbation in practice. An adaptive control scheme is analytically derived using Lyapunov stability theory for a given bound of system perturbation. We accomplish numerical simulation for evaluation of the proposed control system and demonstrate its superiority comparing with the traditional control strategy.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.486-493
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• 2000

This paper presents an application to a multimachine power system of power system stabilizer using revised pole shift adaptive algorithm. Controller parameters are determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameters of controller and overcome the problem of pole placement algorithm, this paper presents pole shift algorithm revised pole shift factor. Also, the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping characteristics. The results tested on a multimachine power system verify that the proposed controller has better dynamic and transient performance than conventional controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.795-803
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• 2015

Autoreclosure provides a means of improving power transmitting ability and system stability. Conventional reclosure adopts the fixed dead time interval strategy, where the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions. However, these simple techniques cannot provide optimal operating performance. This paper presents an adaptive autoreclosure algorithm including variable dead time, optimal reclosure, phase-by-phase reclosure and emergency extended equal-area criterion (EEEAC) algorithm in order to improve system stability. The reclosure algorithm performs the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested using ATP/EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.58-66
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• 2001

This paper presents an application of a newly designed Adaptive Genetic Algorithm (AGA) to solve the Optimal Feeder Routing (OFR) problem for distribution system planning. The main objective of the OFR problem usually is to minimize the total cost that is the sum of investment costs and system operation costs. We propose a properly designed AGA, in this paper, which can handle the horizon-year expansion planning problem of power distribution network in which the location of substation candidates, the location and amount of forecasted demands are given. In the proposed AGA, we applied adaptive operators using specially designed adaptive probabilities. we also a Simplified Load Flow (SLF) technique for radial networks to improve a searching efficiency of AGA. The proposed algorithm has been evaluated with the practical 32, 69 bus test system to show favorable performance. It is also shown that the proposed method for the OFR can also be used for the network reconfiguration problem in distribution system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.311-316
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• 2002

In this paper, an adaptive beamforming algorithm, based on the Minimum Mean Squared Error (MMSE) criterion, is devised fer adaptive antenna applied to an MC-CDMA system. A new method for updating the weight vector is derived. Computer simulations show that proposed algorithm is capable of rejecting co-channel interference that affects the MC-CDMA system. Thus, the BER performance of the MC-CDMA system is improved compared with that of the MC-CDMA system without using adaptive antenna and that of the DS-CDMA system with adaptive antenna in multi-path Ricean fading channel.

• Journal of Welding and Joining
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• v.17 no.6
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• pp.90-99
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• 1999

Significant portion of the total manufacturing time for a pipe fabrication process is spent on the welding following primary machining and fit-up processes. To achieve a reliable weld bead appearance, automatic seam tracking and adaptive control to fill the groove are urgently needed. For the seam tracking in welding processes, the vision sensors have been successfully applied. However, the adaptive filling control of the multi-torches system for the appropriate welded area has not been implemented in the area of SAW(submerged arc welding) by now. The term adaptive control is often used to describe recent advances in welding process control by strictly this only applies to a system which is able to cope with dynamic changes in system performance. In welding applications, the term adaptive control may not imply the conventional control theory definition but may be used in the more descriptive sense to explain the need for the process to adapt to the changing welding conditions. This paper proposed various types of methodologies for obtaining a good bead appearance based on multi-torches welding system with the vision system in SAW. The methodologies for adaptive filling control used welding current/voltage, arc voltage/welding current/wire feed speed combination and welding speed by using vision sensor. It was shown that the algorithm for welding current/voltage combination and welding speed revealed sound weld bead appearance compared with that of voltage/current combination.