• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.688-693
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• 2007

The INS/GPS integration system is designed by employing an adaptive filter that can estimate the measurement noise variance using the residual of the filter. To verify the efficiency of the proposed loosely-coupled INS/GPS integration system, simulation is performed by assuming that GPS information has large position errors. Simulation results show that the proposed integration system with the adaptive filter is more effective in estimating the position and attitude errors than those with the Extended Kalman Filter.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.145-145
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• 2000

In this paper, we propose a hybrid d-step predictor which is composed of an adaptive predictor and a Kalman predictor. We prove the performance limit of the proposed predictor. Simulation is conducted to examine the performance of the proposed predictor. Simulation results show that the proposed combined predictor is superior to the adaptive predictor and the Kalman predictor. Proposed predictor is used for prediction of gun tip vibration of k1 tank. The result is compared with that of conventional adaptive predictor.

• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

• 한국시뮬레이션학회논문지
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• 제8권3호
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• pp.77-89
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• 1999

Simulating rare events, such as probability of cell loss in ATM networks, machine failure in highly reliable systems, requires huge simulation efforts due to the low chance of occurrence. Importance Sampling (IS) has been applied to accelerate the occurrence of rare events. However, it has a drawback of effective biasing scheme to make the estimator of IS unbiased. Adaptive Importance Sampling (AIS) employs an estimated sampling distribution of IS to the system of interest during the course of simulation. We propose Nonparametric Adaptive Importance Sampling (NAIS) technique which is nonparametrical version of AIS. We test NAIS to estimate a probability of rare event in M/M/1 queueing model. Comparing with classical Monte Carlo simulation, the computational efficiency and variance reductions gained via NAIS are substantial. A possible extension of NAIS regarding with random number generation is also discussed.

• 한국시뮬레이션학회논문지
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• 제25권2호
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• pp.63-74
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• 2016

본 연구는 자가-적응 조명 제어 소프트웨어에 대한 시뮬레이션을 수행하고, 이를 통해 실제 시스템의 성능 평가 기준을 명시하는 것을 목적으로 하고 있다. 자가-적응 소프트웨어는 소프트웨어를 작동시키는 과정에서 소프트웨어가 스스로 주변 환경을 모니터링해 환경에 예상하지 못한 변화가 발생한 것을 감지하고, 변화하는 실행 환경에 맞추어 요구사항을 만족시키는 소프트웨어를 의미한다. 본 연구는 IoT(Internet of Things) 환경에서 자가-적응을 수행하는 조명 제어 시스템에 대한 연구이다. 제안하는 시스템은 환경이 변화함에 따라 사용자의 요구사항을 고려해 시스템 스스로의 적응을 수행한다. 이에 대한 시나리오와 시스템 아키텍처 및 평가지표를 소개하며, 이를 기반으로 시뮬레이션을 진행하여 성능 평가를 수행했다.

• 한국인터넷방송통신학회논문지
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• 제17권4호
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• pp.123-128
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• 2017

본 논문은 SMMA (Sliced Multi Modulus Algorithm) 등화 알고리즘에서 등화기의 출력 전력에 비례하는 adaptive modulus와 adaptive stepsize를 적용하므로서 등화 성능을 개선할 수 있는 Hybrid-SMMA 알고리즘에 관한 것이다. 기존 SMMA 알고리즘에서는 등화기의 탭 계수 갱신을 위한 오차 신호를 발생할 때 송신측 신호의 통계 특성치인 modulus를 고정적으로 사용하지만, 제안 Hybrid-SMMA에서는 등화기 출력 신호의 전력에 비례토록 modulus와 오차 신호의 비선형성을 이용하여 stepsize를 적응적으로 변화시킨다. 제안 알고리즘의 개선된 등화 성능을 컴퓨터 시뮬레이션을 통해 확인하였으며, 시뮬레이션 결과 제안 방식이 기존 SMMA보다 모든 성능에서 우월함을 확인하였다.

• 대한원격탐사학회지
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• 제25권5호
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• pp.455-464
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• 2009

Lee(2009)에서 영상 강도를 위해서 lognormal 확률 모형과 영상 texture를 위해서 Markov random field(MRF)에 기반하는 Bayesian 모형을 사용하는 boundary-adaptive despeckling 방법을 제안하였다. 이 방법은 speckle 제거 영상의 최대 사후(maximum a posteriori: MAP) 추정치를 구하기 위해서 Point-Jacobian iteration을 이용한다 인접하고 있는 다른 특성의 지역에 위치한 화소의 값을 사용하는 가능성을 줄이기 위해 Boundary-adaptive algorithm은 경계에 가까울 수록 멀리 떨어진 이웃 화소로부터 정보를 덜 수집하도록 고안된다. 이러한 boundary-adaptive 방법은 전반적으로 simulation 자료를 사용하여 Lee(2009)에서 평가되었고 그리고 제안된 방법의 효험을 증명하였다. 본 연구는 Lee(2009)의 확장 연구로 MAP 추정치를 구하기 반복 algorithm의 계산 효율성을 증가 시키고 noise 제거와 함께 분류를 수행하는 수정 algorithm을 제안한다. Simulation 자료를 사용한 실험을 통해서 boundary-adaption이 분류 오류를 줄여줄 뿐 아니라 더욱 명확한 경계선을 보여준다는 것을 알 수 있다. 또한 영종도 서해안에서 관측된 고해상도 Terra-SAR data에 적용한 결과는 boundary-adaption은 SAR 활용에서 분석의 정확성을 개선 시킬 수 있다는 것을 암시한다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2008년도 춘계학술대회 논문집
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• pp.225-229
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• 2008

We present an intelligent forging simulator AFDEX. The intelligent forging simulator is determined by the adaptive and optimal mesh generation technique and many intelligent application-oriented special functions which minimize the user-intervention during forging simulation. Of course, the solution accuracy should be optimized in the intelligent simulation. We have developed AFDEX to meet the requirement on intelligent simulation. Its characteristics are introduced with the help of typical application examples.

• Journal of Multimedia Information System
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• 제7권4호
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• pp.263-268
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• 2020

This paper introduces an event modeling and simulation system using behavior trees. The system aims to overcome the limitations of existing fixed, simple scenario-based training content, and to extend the behavior of objects to enable various experience deployments. To achieve this goal, we made specific tasks of behavior trees can change according to users' reaction and developed an adaptive simulation module that can analyze and execute behavior trees that changes at runtime. In order to validate our approach, we applied the adaptive behavior tree simulation to the scenarios in our virtual reality simulation-based fire training system we have been developing and demonstrated the implementation results.

• 전기의세계
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• 제30권12호
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.