• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.11a
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• pp.146-146
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• 2007

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1436-1439
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• 1990

Even though the concept "Adaptive" was introduced in the late 50's, the main contribution to adaptive and/or self-tuning control has been made since late 70's. This paper describes the feature of adaptive control simulation package KERICON(I) developed in KERI. Informations on hardware environments, install and testing of a new algorithm and user interfacings are also summarized. The package is written in C language and currently being updated for expert-type adaptive control package (KERICON II).RICON II).

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.134-144
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• 2017

This paper presents an adaptive control strategy for the speed control of a four-phase switched reluctance motor (SRM) in automotive applications. The main objective is to minimize the torque ripples, despite the unstructured uncertainties, time-varying parameters and external load disturbances. The bound of perturbations is not required to be known in the developing of the proposed adaptive-based control method. In order to achieve a smooth control effort, some properties are incorporated and the proposed control algorithm is constructed using the Lyapunov theorem where the closed-loop stability and robust tracking are ensured. The effectiveness of the proposed controller in rejecting high perturbed load torque with smooth control effort is verified with comparing of an adaptive sliding mode control (ASMC) and validated with experimental results.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.38-41
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• 1991

RLS algorithms are required for applications to adaptive line enhancers, adaptive equalizers for voiceband telephone and HF modems, and wide-badn digital spectrum mobile raio in which their convergence time and tracking speed are significant. The fast QR RLS algorithm satisfies above the requirements. Its computational complexity is linearly proportional to the tap number of a filter, N and its performance remains numerically stable. From the result of simumulation, the fast QR RLS algorithm represented Cioffi is better than gradient based algorithm in its initial performance when being applied to an adaptive line enhancer for cancelling noise.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.45-48
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• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• Structural Engineering and Mechanics
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• v.6 no.8
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• pp.955-969
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• 1998

Engineering problems are inherently imprecision tolerant. Biologically inspired soft computing methods are emerging as ideal tools for constructing intelligent engineering systems which employ approximate reasoning and exhibit imprecision tolerance. They also offer built-in mechanisms for dealing with uncertainty. The fundamental issues associated with engineering applications of the emerging soft computing methods are discussed, with emphasis on neural networks. A formalism for neural network representation is presented and recent developments on adaptive modeling of neural networks, specifically nested adaptive neural networks for constitutive modeling are discussed.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.403-407
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• 1999

In this paper we present an architecture, implementation, and performance evaluation of an adaptive communication system (ACS) for wide-area ATM clusters. Our approach capitalizes on thread-based programming model to overlap computation and communication and develop a dynamic message-passing environment with separate data and control paths. This leads to a flexible and adaptive message-passing environment that can support multiple flow control, error control, and multicasting algorithms. We show the performance of ACS applications and compare them with p4, PVM, and MPI applications.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.590-593
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• 2005

Unmanned Helicopter has several abilities such as vertical Take off, hovering, low speed flight at low altitude. Such vehicles are becoming popular in actual applications such as search and rescue, aerial reconnaissance and surveillance. These vehicles also used under risky environments without threatening the life of a pilot. Since a small unmanned helicopter is very sensitive to environmental conditions, it is generally known that the flight control is very difficult problems. The nonlinear adaptive fuzzy controller design procedure and its applications for altitude control of unmanned helicopter were described in the paper. This research was concentrated on describing the design methodologies of altitude controller design for small unmanned helicopter acquiring autonomous take off and vertical movement. The design methodologies and performance of the altitude controller were simulated and verified with an adaptive fuzzy controller. Throughout simulation results, I showed that the proposed adaptive controllers have enhanced control performance such as robustness, effectiveness and safety, in the altitude control of the unmanned helicopter.

• ETRI Journal
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• v.4 no.3
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• pp.18-29
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• 1982

In a block adaptive filtering procedure, the filter coefficients are adjusted once per each output block while maintaining performance comparable to that of widely used LMS adaptive filtering in which the filter coefficients are adjusted once per each output data sample. An efficient implementation of block adaptive filter is possible by means of discrete transform technique which has cyclic convolution property and fast algorithms. In this paper, the block adaptive filtering using Fermat Number Transform (FNT) is investigated to exploit the computational efficiency and less quantization effect on the performance compared with finite precision FFT realization. And this has been verified by computer simulation for several applications including adaptive channel equalizer and system identification.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.99-111
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• 1995

It is shown that the adaptive kernel methods can potentially produce superior density estimates to the fixed one. In using the adaptive estimates, problems pertain to the initial choice of the estimate can be solved by iteration. Also, simultaneous recommended for variety of distributions. Some data-based method for the choice of the parameters are suggested based on simulation study.