• 한국항공우주학회지
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• 제40권4호
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• pp.285-291
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• 2012

본 논문에서는 간섭계 레이더 고도계를 활용한 지형참조항법의 성능을 분석하고자 한다. 간섭계 레이더 고도계는 항체의 주변 지형의 고도 중 가장 높은 값을 측정값으로 취함으로써 항법의 정확성을 향상시키고 있다. 이에 본 연구에서는 간섭계 레이더 고도계의 적용에 따른 새로운 측정 모델을 제시하고 이에 따른 지형참조항법 시스템을 구축하려 한다. 또한 필터에 따른 지형참조항법의 성능 분석을 위하여 확장형 칼만 필터, 무향 칼만 필터, 파티클 필터를 적용하며 여러 환경의 변화에 따른 지형참조항법의 성능을 도출고자 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.177.3-177
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• 2001

In this paper, the design of the in-motion alignment system of Strapdown Inertial Navigation System(SDINS) using Robust Extended Kalman Filter(REKF) is presented. The compensation of errors in the aided navigation system is accomplished by the indirect feedback filtering. The performance of the aided navigation algorithm is very sensitive to the accuracy of the initial estimate, which is the characteristic of the EKF. Unfortunately, the initial attitude error can be very large during the in-motion alignment. To overcome the in-motion alignment under large initial attitude error problem, the REKF using linear robust filtering technique is proposed. The linear robust H$_2$ filter can be adopted for nonlinear ...

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.273-276
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• 1994

It has been known the fact that extended Kalman filter (EKF) is correctly capable of estimating system parameters and state variables by eliminating virtually all influences of structural noises, and fuzzy controller is robust to parameter variations. this paper presents a design method of Reduced-Order EKF and fuzzy controller which consists of the rotor speed and the rotor flux estimation only by measuring stator currents. Experiment results show that both the rotor speed and the rotor flux can be prominently estimated in a wide range of the speed.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.341-347
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• 2022

This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1766-1769
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• 1997

Fast and accurate distillation design requires a model that significantly reduces the problem size withour loss of accruacy is especially suitable for rela-time applicatoins. the reduced order model is obtained by use of Principal Component Anlysis(PCA). Then the extended Kalman filter and the Recursie Predictiuon Error(RPE) mehtod are appliced to identify the model parameters and the feed compostion form the measuremenets of the coumn. as a consequence it is found that the model reduction thechique can account for the dynamics of the rigorous distillation model and not only the model parameters, bu also the feed compostion can be identified efficiently. this technique is applied to industrial operation data verify the performance of reduced order model.

• 로봇학회논문지
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• 제9권4호
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• pp.232-241
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• 2014

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2014년도 추계학술대회 논문집
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• pp.56-57
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• 2014

본 논문에서는 $LiCoO_2$ 원통형(cylindrical)셀을 확장칼만필터(extended Kalman filter; EKF) 추정알고리즘에 적용 시 등가회로모델 차이에 따른 SOC(State-of-charge) 추정성능의 비교 분석을 진행하였다. 첫 번째, 등가회로 모델의 성능을 좌우하는 RC-ladder의 개수에 따른 SOC 추정성능의 차이를 비교하였고, 두 번째, 모델 단순화에 따른 불가피한 모델의 에러를 줄이고자 사용되는 노이즈 모델(noise model) 및 데이터 리젝션(data rejection)의 유무에 따른 SOC 추정성능을 비교분석 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.468-473
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• 1998

A mathematical model was developed for a continuous re-actor in which free radical polymerization of methyl methacrylate (MMA) occurred. Elementary reactions considered in this study were initiation, propagation, termination, and chain transfers to monomer and solvent. The reactor model took into account the density change of the reactor contents and the gel effect. A control system was designed for a continuous reactor using extended Kalman filter (EKF) based non-linear model predictive controller (NLMPC) to control the conversion and the weight average molecular weight of the polymer product. Control input variables were the jacket inlet temperature and the feed flow rate. For the purpose of validation of the control strategy, on-line digital control experiments were conducted with densitometer and viscometer for the measurement of the polymer properties. Despite the com-plex and nonlinear features of the polymerization reaction system, the EKF based NLMPC performed quite satisfactorily for the property control of the continuous polymerization reactor.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 전력전자학술대회 논문집
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• pp.397-398
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• 2015

본 논문은 $LiFePO_4$ 셀의 SOC(State of Charge) 추정에서 가장 중요한 역할을 하는 모델 파라미터인 OCV(Open Circuit Voltage)의 설계에 관한 것이다. $LiFePO_4$ 셀은 히스테리시스 특성 때문에 Charging/Discharging OCV값을 이은 curve인 Major loop만으로는 신뢰도 높은 SOC 추정이 어렵다. 따라서, 기존의 Major loop에 추가적으로 SOC 10% 구간별로 Minor loop을 설계해 줌으로써 배터리 모델링의 정확도를 높이고, 이를 최종적으로 EKF(Extended Kalman Filter)알고리즘을 이용하여 SOC 추정으로 해봄으로써 정확도 향상을 비교해 보고 분석해 보고자 한다.

• 한국자동차공학회논문집
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• 제8권4호
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.