• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.741-746
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• 2004

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.29-34
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• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.158-165
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• 2019

Knowledge based system includes tools for constructing, testing, validating and refining the system along with user interfaces. An important issue in the design of a complete knowledge based system is the ability to produce explanations. Explanations are not just a series of rules involved in reasoning track. More detailed and explicit form of explanations is required not only for reliable reasoning but also for maintainability of the knowledge based system. This requires the explanation mechanisms to extend from knowledge oriented analysis to task oriented explanations. The explicit modeling of problem solving structures is suggested for explanation generation as well as for efficient and effective reasoning. Unlike other explanation scheme such as feedback explanation, the detailed, smaller and explicit representation of problem solving constructs can provide the system with capability of quality explanation. As a key step to development for explanation scheme, the problem solving methods are broken down into a finer grained problem solving primitives. The system records all the steps with problem solving primitives and knowledge involved in the reasoning. These are used to validate the conclusion of the consultation through explanations. The system provides user interfaces and uses specific templates for generating explanation text.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.79-100
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• 2004

As a part of ebXML(Electronic Business using eXtensible Markup Language) framework, BPSS(Business Process Specification Schema) has been provided to support the direct specification of the set of elements required to configure a runtime system in order to execute a set of ebXML business transactions. The BPS,' is available in two stand-alone representations, a UML version and an XML version. Due to the limitations of UML notations and XML syntax, however, current ebXML BPSS specification fails to specify formal semantic constraints completely. In this study, we propose a constraint classification scheme for the BPSS specification and describe how to formally represent those semantic constraints using OCL(Object Constraint Language). As a way to validate p Business Process Specification(BPS) with the formal semantic constraints, we suggest a rule-based approach to represent the formal constraints and demonstrate its detailed mechanism for applying the rule-based constraints to the BPS with a prototype implementation.

• Journal of Power Electronics
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• v.15 no.1
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• pp.65-77
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• 2015

Resonant converters are well suited for induction heating (IH) applications due to their advantages such as efficiency and power density. The control systems of these appliances should provide smooth and wide power control with fewer losses. In this paper, a simple phase locked loop (PLL) based variable duty cycle (VDC) pulse density modulation (PDM) power control scheme for use in class-D inverters for IH loads is proposed. This VDC PDM control method provides a wide power control range. This control scheme also achieves stable and efficient Zero-Voltage-Switching (ZVS) operation over a wide load range. Analysis and modeling of an IH load is done to perform a time domain simulation. The design and output power analysis of a class-D inverter are done for both the conventional pulse width modulation (PWM) and the proposed PLL based VDC PDM methods. The control principles of the proposed method are described in detail. The validity of the proposed control scheme is verified through MATLAB simulations. The PLL loop maintains operation closer to the resonant frequency irrespective of variations in the load parameters. The proposed control scheme provides a linear output power variation to simplify the control logic. A prototype of the class-D inverter system is implemented to validate the simulation results.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.298-304
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• 2006

This paper proposes a ray-based forward modeling scheme which is suitable for the shallow water acoustic wave propagation simulations. The proposed model comprises of ray tracings for the layered media of which sound speed profiles are interpolated linearly. considerations of plane and spherical wave reflection coefficients. and calculations of the phases and the amplitudes of eigen rays. The main characteristic of the scheme is fast simulation time due to direct calculation of the broad-band time signals in the time-domain, i.e. without transformation of the frequency-domain solutions to the time si 밍 131s. Finally, we applied the model to 4-types of test environments and compared the resulting signals with those of ORCA and Ram in order to validate the proposed model.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.141-150
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• 2012

The present study examines an efficient congestion management system compatible with the evolving environment. The key is to build an information model shared and exchanged for marketbased solutions to alleviate congestion. Traditional methods for congestion management can be classified into two categories, i.e., the centralized scheme and the decentralized scheme, depending on the extent to which the independent system operator (ISO) is involved in market participants' (MPs) activities. Although the centralized scheme is more appropriate for providing reliable system operation and relieving congestion in near real-time, the decentralized scheme is preferred for supporting efficient market operation. The minimum set of information between the ISO and MPs for decentralized scheme is identified: i) congestion-based zone, ii) Power Transfer Distribution Factors, and iii) transmission congestion cost. The mathematical modeling of the proposed information is expressed, considering its process of making effective use of information. Numerical analysis is conducted to demonstrate both cost minimization from the MP perspective and the reliability enhancement from the ISO perspective based on the proposed information exchange scheme.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.67-79
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• 2003

An efficient mobility management for mobile stations plays an important role in mobile communication networks. Even though many a mobility management schemes have been proposed, most of mobile communication networks adopt the mobility scheme based on zone-based registration. This paper studies the mobility management scheme that combines zone-based registration and 2-step selective paging. We assume cell by cell registration area, not ring by ring registration area of previous studies, and set up a new mobility model based on 2-dimensional random walk model considering the characteristic of zone-based registration to evaluate its performance exactly. We provide numerical results using proposed model to demonstrate the performance of zone-based registration and 2-step selective paging under various circumstances.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1145-1150
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• 1993

In this paper, two methods of fuzzy modeling are prsented to describe the input-output relationship effectively based on relation characteristics utilizing simplified reasoning and neuro-fuzzy reasoning. The methods of modeling by the simplified reasoning and the neuro-fuzzy reasoning are used when the input-output relation of a system is 'crisp' and 'fuzzy', respectively. The structure and the parameter identification in the modeling method by the simplified reasoning are carried out by means of FCM clustering and the proposed GA hybrid scheme, respectively. The structure and the parameter identification in the modeling method by the neuro-fuzzy reasoning are carried out by means of GA and BP algorithm, respectively. The feasibility of the proposed methods are evaluated through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.635-639
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.