• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.1989-1996
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• 2002

Extended Kalman Filter(EKF) is used to estimate friction and spring characteristics on the swash plate of a variable displacement pump. In earlier studies, the feasibility of the approach was established using simulation studies to establish limits of accuracy for the EKF approach when it was applied to an ideal situation. In this study, the EKF is applied to an experimental system and the issue of re liability in estimation of certain pump parameters is addressed. In addition, an approach to assign values to accommodate convergence of the EKF is considered. A special experimental system was set up to facilitate the measurement of certain states to enhance the EKF approach. Estimated parameters show ed some scatter about a specified operating point but in general, were reasonably repeatable. The study also showed that changes in the system parameters could be accurately tracked.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.98-105
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• 2024

Due to the low accuracy of measured data obtained from low-cost GNSS and IMU devices, it was hard to secure the required accuracy of the measured position and heading angle for autonomous navigation which was conducted by a model-scale marine mobility. In this paper, a localization technique using the Extended Kalman Filter (EKF) is proposed for coping with the issue. First of all, a position and heading angle estimator is developed using EKF with the assumption of a point mass model. Second, the measured data from GNSS and IMU, including position, heading angle, and velocity are used for the estimator. In addition, the heading angle is additionally obtained by comparing the LiDAR point cloud with map information for a temporal water tank. The newly acquired heading angle is integrated into the estimator as an additional measurement to correct the inaccuracy in the heading angle measured from the IMU. The effectiveness of the proposed approach is investigated using data acquired from preliminary tests of the model-scale autonomous marine mobility.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.1-16
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• 2008

LBS (Location Based Service) cannot be realized unless we can obtain the user's current location. Therefore, in order to realize indoor LBS, many researchers have been working on WLAN (Wireless Local Area Network) based indoor positioning and tracking. Meanwhile, Kalman filter has been widely used in the field of GPS based outdoor user tracking. The main purpose of this paper is proposing an extended Kalman filter method for indoor tracking. Our experimental results show that Kalman filter can be used to improve the accuracy of the measured tracks and the track can be further improved by making use of the map information.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.123-129
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• 2001

Recent requirements for the fast and accurate motion in industrial robot manipulators need more advanced control tech-niques. To satisfy the requirements, importance of force control is being continuously increased and the expensive force sensor is usually installed to obtain the contact force information in practice. This information is indispensable for the force control of maintaining the desired contact force. However, the sensor cost is too high to be used in industrial applications. In this paper, it is proposed to estimated the contact force occurring between the end-effector of 2 DOF robots and environ-ment. The contact force estimation system is developed based on the static and dynamic models of 2 DOF robot manipula-tors. where the contact force is described with respect to the link torque. The Extended Kalman Filter is designed and its performance is verified in simulations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.14-19
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• 2000

Recent requirements for the fast and accurate motion in industrial robot manipulator need more advanced control techniques. To satisfy the requirements, importance of the force control is being continuously increased and the expensive force sensor is usually installed to obtain the contact force information in practice. This information is indispensable for the force control of maintaining the desired contact force. However the sensor cost is too high to be used in industrial applications. In this paper, it is proposed to estimate the contact force occurred between the end-effector of 2 DOF robots and environment. The contact force estimation system is developed based on the static and dynamic models of 2 DOF robot manipulators, where the contact force is described with respect to the link torque. The Extended Kalman Filter is designed and its performance is verified in simulations.

• Journal of IKEEE
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• v.17 no.4
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• pp.440-445
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• 2013

This paper proposes a local estimation system which combines Cell Divide Algorithm with low-cost GPS/INS fused by Extended Kalman Filter(EKF) for localization of Quad-rotor when it returns to the departure point. In the research, the low-cost GPS and INS are fused by EKF to reduce the local error of low-cost GPS and the accumulative error of INS due to continuous integration of sensor error values. When the Quad-rotor returns to the departure point in the fastest path, a moving path can be known because it moves straight, where Cell Divide Algorithm is used to divide moving route into the cells. Then it determines the closest position of data of GPS/INS system fused by EKF to obtain the improved local data. The proposed system was verified through comparing experimental localization results obtained by using GPS, GPS/INS and GPS/INS with Cell Divide Algorithm respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• Journal of Astronomy and Space Sciences
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• v.12 no.1
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• pp.143-156
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• 1995

Using a directional antenna, the Doppler effect of satellites can be detected and the orbital elements can be obtained by the Extended Kalman Filter with the observed frequency shift data. We obtained the orbital elements of NOAA-11 by the application of the Extended Kalman Filter type algorithm to the Doppler shift data of NOAA-11d and discussed the accuracy and the credibility of this algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2A
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• pp.89-96
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• 2011

The damping ratio as an index of bridge vibration could be considered as one of the important dynamic characteristics of a suspension bridge. But estimating of damping ratio on an existing suspension bridge under ambient vibration condition could be a laborious task. Moreover, it is not simple to directly distinguish aerodynamic damping and friction damping from apparent damping. According to previous studies, the aerodynamic damping properties can be linearly affected by wind speed level, and apparent damping ratio can be affected by amplitude of vibration. Therefore, in this article, the relationships among damping ratio, wind speed level and amplitude of acceleration were studied for separating extract aerodynamic damping and friction damping from apparent damping. Damping ratios on Sorok Bridge, a suspension bridge which is a located in Go-Heung, Korea, were estimated by two different methods as using Hilbert transform and extended Kalman filter which were well known as effective estimation methods for non-linear state. It was possible to distinguish aerodynamic damping and friction damping from apparent damping using averaged normal components of wind speed, RMQ values of acceleration, and estimated damping ratios from wind-induced vibration responses and vehicle loading responses.