• Journal of Institute of Control, Robotics and Systems
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• 제3권3호
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• pp.238-243
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• 1997

A new transfer alignment algorithm using the velocity and the quaternion partial matching methods is proposed to reduce the effect of a ship's Y-axis flexure on the performance of azimuth error estimation of Kalman filter. The simulation results show that it can significantly reduce the effect of Y-axis flexure on error estimation by the transfer alignment algorithm. As its results, azimuth transfer alignment error is reached up to 3 mrad under proper roll and pitch attitude motion of the ship.

• Multiscale and Multiphysics Mechanics
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• 제1권3호
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• pp.261-270
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• 2016

The longitudinal velocity (forward speed) having significant importance in proper running of railway wheelset on track, depends greatly upon the adhesion ratio and creep analysis by implementation of suitable dynamic system on contamination. The wet track condition causes slip and slide of vehicle on railway tracking, whereas high speed may also increase slip and skidding to severe wear and deterioration of mechanical parts. The basic aim of this research is to design appropriate model aimed estimator that can be used to control railway vehicle forward velocity to avoid slip. For the filtration of disturbance procured during running of vehicle, the kalman filter is applied to estimate the actual signal on preferered samples of creep co-efficient for observing the applied attitude of noise. Thus error level is detected on higher and lower co-efficient of creep to analyze adhesion to avoid slip and sliding. The skidding is usually occurred due to higher forward speed owing to procured disturbance. This paper guides to minimize the noise and error based upon creep coefficient.

• The Transactions of the Korean Institute of Electrical Engineers A
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• 제48권5호
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• pp.607-614
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• 1999

This paper deals with the design problem of the state estimator for servo system. The servo system has input time delay which depends on the computational time of control algorithm. The delayed input is a factor that brings out the state estimation error. So in order to reduce the state estimation error of the system, we propose a state estimator in which the delayed input of the system is considered. For this purpose, discrete time state space model is established accounting for the delayed input and a state estimator is designed based on this model. Kalman filter algorithm is employed in the design of the state estimator. The proposed estimator is used in the speed control of servo system with delayed input. Performance of the proposed state estimator is exemplified via simulations and experiments for servo system. Also, robustness of the proposed estimator to modeling error by variation of the system parameters is also shown in simulations.

• The Transactions of the Korean Institute of Electrical Engineers B
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• 제48권9호
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• pp.517-522
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• 1999

This paper addresses the issue of current sampling in a high performance AC drive system fed by a discontinuous PWM inverter. The effect of the sampling error due to the measurement delay produced by an input stage low pass filter and an A/D converter is described in the case of discontinuous PWM. To compensate for the sampling error, a method to estimate the delay time of the whole measurement system based on the measured current is proposed and its effectiveness is verified by experimental results. The proposed algorithm can automatically estimate the system delay introduced by the low pass filter and the A/D converter at the commissioning stage. By delaying the current sampling by the estimated value, experimental results indicate that more than 50% reduction of current ripple can be achieved.

• Journal of Mechanical Science and Technology
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• 제20권12호
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• pp.2043-2051
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• 2006

This paper considered identification of vibration characteristics of flexible structure with vector channel periodic lattice filter. We present an algorithm for AR coefficients for the vector-channel lattice filters, and characteristic equation and transfer function are derived from these coefficients. Vibration lattice filter is then constructed from the vector channel lattice filter, and performance of this vibration filter is tested with a test signal which is a combination of many sine waves to compare the performance of scalar and vector channel lattice. Also it is applied to the cantilever data to identify properties of the system, such as natural frequencies and damping ratios, to show its performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1897-1902
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• 2005

The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1450-1455
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• 2005

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure land DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• Journal of Institute of Control, Robotics and Systems
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• 제17권2호
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• pp.125-130
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• 2011

This paper shows a method to design complementary filter using least square. The complementary filter is one of useful filters estimating angle. The basic concept of this filter is to enhance advantages of each sensor that angle detecting using a gyroscope has good accuracy at a high frequency and an accelerometer at a low frequency. When designing complementary filter, the most commonly used method is using cut-off frequency. However, it may be not easy to obtain a cut-off frequency. This paper presents a systematic method to determine the coefficients of the complementary filter using well-known linear least squares minimizing error between estimating angle and true angle.

• Journal of the Korea Institute of Military Science and Technology
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• 제1권1호
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• pp.201-210
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• 1998

Inertial Navigation System(INS) can provide the vehicle position and velocity information using inertial sensor outputs without the use of external aids. Unfortunately INS navigation error increases with time due to inertial sensor errors, and therefore it is desirable to combine INS with external aids such as GPS, TACAN, OMEGA, and etc.. In this paper we propose an integration algorithm of commercial GPS/GLONASS and INS where an adaptive filter for signal processing of GPS/GLONASS receiver and the 12th order Kalman filter for aided strapdown INS(SDINS) we employed. Simulation results show that the proposed adaptive filter can effectively remove a randomly occurring abrupt jump due to sudden corruption of the received satellite signal and that the Kalman filter performs satisfactorily.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.125-130
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• 1991

This paper presents a tracking filter using pseudomeasurements in an estimated line-of-sight Cartesian coordinate system(ELCCS) whose x-axis is on the line-of-sight to an estimated target position. A target dynamics model and a measurement equation in the ELCCS are derived first and then a tracking filter in the ELCCS named moving coordinate tracking filter(MCTF) is proposed. It is shown that this MCTF is equivalent to a Kalman filter in the inertial Cartesian coordinate system which is widely used in the target tracking system. By approximating the MCTF for a pseudomeasurement noise and an error covariance matrix in the ELCCS, decoupling of three axes can be achieved. In this case, named decoupled moving coordinate tracking filter(DMCTF), computation time can be drastically reduced by utilizing its parallel structure. Finally, the stochastic properties of the MCTF and DMCTF are presented. Especially, a sufficient condition of nondestabilizing deviation for the DMCTF is proposed. The performance of the MCTF and DMCTF are compared with a conventional Kalman tracking filter.