• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.344-347
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• 1995

The standard estimation and filtering theory are well known and has recently been incorporated with the H$_{\infty}$ optimization techniques where the parametrizations of all estimators and filters are utilized. The issue of reducing its order is always of interest. This paper presents a method for synthesizing low-order stable state estimators. The method presented in this paper is based on the utilization of a free parameter function contained in the parametrization of all state estimators. The results obtained in the paper are compared with standard results on low-order estimators. Both results are shown to be the same in a sense of its orders, but the approaches taken are largely different. It is also shown in the paper that the method can easily and directly be extended to the Kalman filters and the H$_{\infty}$ (sub)optimal filters. Consequently, the orders of all state estimators, Kalman filters, and H$_{\infty}$ filters are shown to be reduced down to the number of states minus the number of outputs, respectively.ly.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.683-688
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• 2017

The unscented Kalman filter features a direct transforming process involving unscented transformation for removing the linearization process error that may occur in the extended Kalman filter. This paper proposes a reduced-order unscented Kalman filter for the sensorless control of a permanent magnet synchronous motor. The proposed method can reduce the computational load without degrading the accuracy compared to the conventional Kalman filters. Moreover, the proposed method can directly estimate the electrical rotor position and speed without a back-electromotive force. The proposed Kalman filter for the sensorless control of a permanent magnet synchronous motor is verified through the simulation and experimentation. The performance of the proposed method is evaluated over a wide range of operations, such as forward and reverse rotations in low and high speeds including the detuning parameters.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.

• 한국해양공학회지
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• 제2권2호
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• pp.37-45
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• 1988

A dynamically positioned vessel must be capable of maintaining a specified position and direction by controlling the thruster devices. The motions of a vessel are often assuned to tne sum of low frequency(LF)motions and high frequency(HF)motions. The former is mainly due to wind, current and second order wave forces, while the latter is mainly due to first order wave forces. In order to avoid the high frequency thruser modulation, the control system must include filters to estimate the low frequency motions from the measured motion signals, This paper presents a control system based on Kalman filtering technique and optimal control tyeory. Using the combined kalmam filter, LF motion estimates and HF ones are achieved from the motion measurement of the vessel. The estimated low frequency motions are used as inputs to the dynamic positioning system. The thruster modulation is minimized using the optimal control theory; Linear Quadratic Gaussian(LQG)controller. The performances of the Kalman filter and the dynamic positioned vessel are investigated by computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2348-2360
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• 2023

As science and technology evolve, object detection of moving objects has been widely used in the context of machine learning and artificial intelligence. Traditional moving object detection algorithms, however, are characterized by relatively poor real-time performance and low accuracy in detecting moving objects. To tackle this issue, this manuscript proposes a modified Kalman filter algorithm, which aims to expand the equations of the system with the Taylor series first, ignoring the higher order terms of the second order and above, when the nonlinear system is close to the linear form, then it uses standard Kalman filter algorithms to measure the situation of the system. which can not only detect moving objects accurately but also has better real-time performance and can be employed to predict the trajectory of moving objects. Meanwhile, the accuracy and real-time performance of the algorithm were experimentally verified.

• 한국항공우주학회지
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• 제34권4호
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• pp.47-52
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• 2006

불규칙 혼합잡음의 등가 ARMA 모델 표현을 사용하여 자이로의 불규칙 혼합잡음을 고려하는 보조항법시스템 칼만필터 설계 방법을 제안한다. 필터 설계 절차는 먼저 보조항법 시스템에 사용되는 필터는 간접 되먹임 칼만필터임을 고려하여 등가 ARMA 모델로 표현된 자이로 불규칙 잡음의 시간 차분을 구한다. 다음으로 시간 차분된 ARMA 모델을 상태 방정식으로 표현하는데 AR과 MA 차수에 따라 두 가지로 나누어진다. 먼저 AR 차수가 큰 경우 가제어 혹은 가관측 특이형태를 사용한다. MA 차수가 큰 경우에는 몇 단계 이후의 예측치를 상태변수로 하는 상태방정식을 사용하는데, 이때 자이로 출력을 보상하는 값에 따라 다시 고차수 필터와 저차수 필터로 구분된다. 마지막으로 자이로 불규칙 잡음을 보조항법시스템 칼만필터에 포함시켜 최종적인 필터 모델을 얻는다. 시뮬레이션 결과를 통하여 제안된 고차수 및 저차수 필터 모두 혼합잡음을 백색잡음으로 간주한 기존의 필터보다 항법오차를 감소시킬 수 있음을 보임으로써 그 효용성을 제시한다.

• 대한조선학회논문집
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• 제40권1호
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• pp.8-19
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• 2003

Special purpose vessels such as drillship and ocean research vessels install the DPS(Dynamic Positioning System) to maintain the position and heading for long-time operation. This paper deals with the design parameters for the control theory and filter algorithms of DP system. for the environmental loadings wind forces, current forces and wave forces were considered. In order to estimate the low frequency motions without first-order wave motion, the Kalman filter was used and it was assumed that the first-order wave forces correspond to system noises and first-order wave motions are measurement noises. In this simulation, the length of research vessel is 65 meters and it has four thrusters to maintain the position. The ability of keeping position and heading was confirmed. For the calculation of thruster input the LQR and LOI control theory were adopted and the effects of gain were investigated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.990-994
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• 2003

When the low cost IMU is used, the result of the stationary self alignment is not suitable for navigation. In this paper, an in-motion alignment method is proposed to obtain an accurate initial attitude of a low cost IMU based GPS/INS integration system. To design Kalman filter for alignment, large heading error model is introduced. And then Kalman filter is designed to estimate initial attitude error as the indirect feedback filter. In order to assess performance of the alignment method, computer simulations are carried out. The simulation results show that initial attitude error rapidly reduces.

• 한국구조물진단유지관리공학회 논문집
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• 제19권4호
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• pp.43-48
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• 2015

본 연구에서는 지진계 센서의 동적범위를 향상시키는 새로운 방법을 제안하였다. 먼저, 센서에 포함된 저주파수 대역 잡음을 ARMA(Auto Regresive Moving Average) 모델로 모델링하고 시스템 식별 방법으로 그 모델을 식별한다. 다음으로, 모델링된 잡음과 지진파 입력을 칼만필터 식에 포함하여 칼만필터에 의한 지진파입력을 추정한다. 제안한 방법을 새로이 개발된 MEMS 기반 3축 가속도 형태의 지진계에 적용하여 성능을 검증하였다. 시험 결과는 제안한 방법이 단순한 LPF(Low Pass Filter)를 사용한 경우에 비해 동적범위를 개선시킴을 보여준다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.184-187
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• 1997

In terms of a system identification, we present a method for autoregressive(AR) modelling of variious biomedical signal. Model order is estimated fly low rank approximation and coefficients are determined by innovation processes of Kalman filter derivation. An application of the method is given for visual evoked potentials.