• 한국기계가공학회지
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• 제15권2호
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.433-436
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• 2003

The estimation of the position and the orientation for the mobile robot constitutes an important problem in mobile robot navigation. Although the odometry can be used to describe the motions of the mobile robots, there inherently exist the gaps between the real robots and the mathematical model, which may be caused by a number of error sources contaminating the encoder outputs. Hence, applying the standard extended Kalman filter for the nominal model is not supposed to give the satisfactory performance. As a solution to this problem, a new robust extended Kalman filter is proposed based on the Krein space approach. We consider the uncertain discrete time nonlinear model of the mobile robot that contains the uncertainties represented as sum quadratic constraints. The proposed robust filter has the merit of being constructed by the same recursive structure as the standard extended Kalman filter and can, therefore, be easily designed to effectively account for the uncertainties. The simulations will be given to verify the robustness against the parameter variation as veil as the reliable performance of the proposed robust filter.

• 정보처리학회논문지B
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• 제12B권5호
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• pp.567-576
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• 2005

다중영상으로부터 투사 선분을 이용하여 3D 모델을 생성하고 각 면의 텍스쳐를 획득하는 구조 복원 기법을 제안한다 사용자는 매우 단순한 절차를 통해 정확한 3D 모델 데이터를 획득할 수 있다. 모델 파라메터 추정을 위해 내재된 비선형 최적화 방법은 사용자 지정 영상 선분과 모델의 투사 선분의 거리를 최소화하는 방법에 기반하고 있다. 모델링 기법의 기능적 주요 목표는 형상이 포함된 다중 영상으로부터 그 형상의 3차원 구조를 복원하고 각 면의 텍스쳐를 생성하는 것이다. 본 연구에서는 3D 정형체를 사용하여 사용의 편리성을 증대시킬 수 있고 정형체의 파라메터의 오차를 최소화하여 복원된 구조의 정확성을 높이는 방법을 제시한다. 제안된 방법은 유한 선분에 기반한 오차 함수를 도입하여 무한 직선에 기반한 방법보다 정확한 모델링이 가능하다. 제안된 방법을 다양한 실제 영상에 적용한 실험 결과를 제시하고 다중 영상기반 모델링 도구의 개발 과정에서의 기술적인 문제점과 해결책을 기술한다.

• 한국정보전자통신기술학회논문지
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• 제12권3호
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• pp.211-217
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• 2019

본 연구에서는 NHPP 모형을 적용한 Type-2 Gumbel 수명분포의 형상모수 변화에 따른 소프트웨어 개발비용모형에 관한 속성을 비교, 분석하였다. 소프트웨어 고장현상을 분석하기 위하여 모수추정은 최우추정법을 적용하였고, 비선형 방정식의 계산은 이분법을 사용하였다, 그 결과, 형상모수의 변화에 따른 비용곡선의 속성을 비교하였을 때 형상모수가 클수록, 소프트웨어 개발비용이 적고 또한, 방출시간도 가장 빠르다는 것을 알 수 있었다. 본 연구를 통하여, 소프트웨어 개발자들에게 소프트웨어 형상모수 변화에 따른 개발비용을 탐색하는데 도움을 줄 수 있으며, 더불어 소프트웨어 개발비용에 관한 속성을 파악하는데 필요한 사전정보을 제공할 수 있을 것으로 기대한다.

• Journal of Electrical Engineering and Technology
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• 제1권2호
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• pp.161-169
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• 2006

Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1137-1139
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• 2002

In this paper, recurrent artificial neural network (RNN) based self tuning speed controller is proposed for the high performance drives of induction motor. RNN provides a nonlinear modeling of motor drive system and could give the information of the load variation, system noise and parameter variation of induction motor to the controller through the on-line estimated weights of corresponding RNN. Thus, proposed self tuning controller can change gains of the controller according to system conditions. The gain is composed with the weights of RNN. For the on-line estimation of the weights of RNN, extended kalman filter (EKF) algorithm is used. Self tuning controller that is adequate for the speed control of induction motor is designed. The availability of the proposed controller is verified through the MATLAB simulation with the comparison of conventional PI controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.349-351
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• 2004

The classical dynamic backpropagation learning algorithm has the problems of learning speed and the determine of learning parameter. The Extend Kalman Filter(EKF) is used effectively for a state estimation method for a non linear dynamic system. This paper presents a learning algorithm using Dual Extended Kalman Filter(DEKF) for Fully Recurrent Neural Network(FRNN). This DEKF learning algorithm gives the minimum variance estimate of the weights and the hidden outputs. The proposed DEKF learning algorithm is applied to the system identification of a nonlinear SISO system and compared with dynamic backpropagation learning algorithm.

• The Korean Journal of Physiology and Pharmacology
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• 제16권2호
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• pp.97-106
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• 2012

The pharmacokinetics/pharmacodynamics analysis software NONMEM$^{(R)}$ output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM$^{(R)}$ VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.

• 한국군사과학기술학회지
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• 제4권2호
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• pp.179-188
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• 2001

The objective of this paper is to design and implement sliding mode control scheme for an actuation system using BLDC motor. Since the dynamic characteristics of this system with unknown disturbance and parameter variations are very complicated and highly nonlinear, the conventional linear control approaches may not guarantee satisfactory control performances. In order to improve the dynamic performances of this system, a model following sliding mode control(MFSMC) with perturbation estimation approach is designed and implemented. It eliminates the conventional requirements for the knowledge of uncertainty upper boundary. The effectiveness of this control approach is verified by comparison with a PID control through a series of simulation and experimental studies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.878-883
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• 1990

There have been many approaches to solve the disturbance rejection problem in the control of LTI systems with state independent disturbances or possibly nonlinear state dependent disturbances. From the view point of each actuator, robot manipulators can be modeled as the second class of systems. With this model, M.Nakao et al. [1] introduced a decentralized control scheme based on interference estimation which is simple in its implementation and robust to the coupled dynamics and parameter variations. This paper systematically generalizes the control scheme to arbitrary finite dimensional LTI systems with disturbances. In doing so, we develop a disturbance observer theory for solving the disturbance rejection problem. We also present a discrete version of the theory with discussion of sampling and time-delay effects.