• 한국정보통신학회논문지
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• 제10권7호
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• pp.1332-1337
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• 2006

이동로봇의 위치추정오차를 검출하는 방법으로 칼만필터의 잔류오차를 최소적응알고리즘으로 검사하여 시스템의 이상유무를 확인할 수 있음을 알아보았다. 이동로봇의 이상유무판별에 칼만필터를 적용하기 위한 모델로는 위치이동에 기여하는모터부분의 모델만을 사용하였고, 칼만필터의 잔류오차에 나타나는 바이어스성분의 검출로 이상유무를 판별할 수 있음을 확인하였다. 이동로봇의 동특성모델을 이용하여 이동로봇의 위치추정에 나타나는 오차를 판별할 수 있는 제안된 방법은 다른 부가적인 외부장치가 없이 사용될 수 있는 장점이 있다 . 칼만필터는 모터의 구동전류를 추정하고, 이 잔류오차에 적응자기동조필터를 적용하여 백색잡음의 성질을 지닌 잔류오차를 판별하게 된다. 이동로봇의 모델에 가능한 상황을 가정하여 구성한 시뮬레이션의 결과들은 제안된 방법이 위치추정 오차의 판별에 사용될 수 있음을 보여주고 있다.

• 한국전자통신학회논문지
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• 제8권12호
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• pp.1865-1874
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• 2013

본 논문은 IPMSM(Interior Permanent Magnet Synchronous Motor)의 센서리스 운전을 위해 엔센티드 칼만필터를 기반으로 하는 속도와 위치 추정기의 설계방법을 제안한다. 제안된 방법은 회전축에 동기하여 설계된 관측기에 비해, 간단한 전류계측이 가능하고 관측기의 비선형 항이 포함되도록 상태 추정기를 설계하였다. 제어기는 비선형 백스텝핑 제어기법으로 구성하고, 추정된 속도와 위치정보로 속도와 전류제어를 수행하였다. 설계된 추정기의 성능은 시뮬레이션을 통해 dq축에 동기하여 설계된 추정기의 성능과 비교 검증하였다.

• 대한전기학회논문지:전력기술부문A
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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.

• 소음진동
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• 제11권1호
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• pp.68-75
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• 2001

A method for actively controlling dynamic reaction forces in flexible structures subject to persistent excitations is presented. Since reaction forces are not directly measured in flexible structures, reaction forces are estimated by using the Kalman filter. The estimated reaction force is used as an error signal in the adaptive feedforward disturbance cancellation controller. In order to compensate the static effect of the truncated modes in the reaction forces, the residual flexibility matrix is used with the Kalman filter. The paper presents the formulation of the reaction forces in conjunction with the Kalman filter estimator and the adaptive feedforward controller. The results show that the dynamic reaction forces at its supports in a flexible beam test rir are well suppressed.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2001년도 춘계학술대회 논문집
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• pp.180-189
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• 2001

In this study, recently developed unscented Kalman filter (UKF) technique is studied for identification of nonlinear structural dynamic systems as an alternative to the extended Kalman filter (EKF). The EKF, which was originally developed as a state estimator for nonlinear systems, has been frequently employed for parameter identification by introducing the state vector augmented with the unknown parameters to be identified. However, the EKF has several drawbacks such as biased estimations and erroneous estimations especially for highly nonlinear dynamic systems due to its crude linearization scheme. To overcome the weak points of the EKF, the UKF was recently developed as a state estimator. Numerical simulation studies have been carried out on nonlinear SDOF system and nonlinear MDOF system. The results from a series of numerical simulations indicate that the UKF is superior to the EKF in the system identification of nonlinear dynamic systems especially highly nonlinear systems.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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• pp.117-126
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• 2001

In this study, the recently developed unscented Kalman filter (UKF) technique is studied for identification of nonlinear structural dynamic systems as an alternative to the extended Kalman filter (EKF). The EKF, which was originally developed as a state estimator for nonlinear systems, has been frequently employed for parameter identification by introducing the state vector augmented with the unknown parameters to be identified. However, the EKF has several drawbacks such as biased estimations and erroneous estimations especially for highly nonlinear dynamic systems due to its crude linearization scheme. To overcome the weak points of the EKF, the UKF was recently developed as a state estimator. Numerical simulation studies have been carried out on nonlinear SDOF system and nonlinear MDOF system. The results from a series of numerical simulations indicate that the UKF is superior to the EKF in the system identification of nonlinear dynamic systems especially highly nonlinear systems.

• 한국자동차공학회논문집
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• 제19권4호
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• pp.38-46
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• 2011

This paper presents roll angle estimator which used Kalman filter. Recently, the uses of the ELSD (Electronic Limited Slip Differential) and TVD(Torque Vectoring Differential) for vehicle yaw control are studied in many researches. However the roll angle can be negative effect of ELSD and TVD control. Therefore the information of roll angle can be used for vehicle yaw control. Moreover it can be used for rollover prevent control. Recently, most of the vehicles use lateral acceleration and yaw rate sensor. In this paper, design of Kalman filter which used lateral acceleration and yaw rate information is developed. In this paper, in order to verify the estimator ability, the CarSim and Matlab/Simulink are used.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.1024-1030
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• 2001

In this paper, a horizontal LOS(line of sight) rate estimator for conventional sea skimming ASM(anti-ship missile) is proposed. A LOS rate dynamics model for a 2-axis gimbal system and the homing geometry is derived. A new LOS rate estimator is proposed by applying the Kalman filter theory to the LOS rate dynamics model. The proposed filter estimates LOS rates by taking roll motions into account. Simulation results show that the proposed filter produces smaller estimation errors than a conventional method.

• Structural Engineering and Mechanics
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• 제34권1호
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• pp.1-14
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• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.996-1003
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• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.