• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.320-326
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• 2008

This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1067-1075
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• 2016

This paper presents an adaptive observer-based approach to estimate voltage parameters, including frequency, amplitude, and phase angle, for single-phase power systems. In contrast to most existing estimation methods of grid voltage parameters, in this study, grid voltage is treated as a dynamic system related to an unknown grid frequency. Based on adaptive observer theory, a full-order adaptive observer is proposed to estimate voltage parameters. A Lyapunov function-based argument is employed to ensure that the proposed estimation method of voltage parameters has zero steady-state error, even when frequency varies or phase angle jumps significantly. Meanwhile, a reduced-order adaptive observer is designed as the simplified version of the proposed full-order observer. Compared with the frequency-adaptive virtual flux estimation, the proposed adaptive observers exhibit better dynamic response to track the actual grid voltage frequency, amplitude, and phase angle. Simulations and experiments have been conducted to validate the effectiveness of the proposed observers.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1269-1271
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• 2009

We had proposed fast thermal stress estimation methodology for the components on system board when the system is stationary within specific ambient air temperature. Now, we will propose one efficient thermal stress estimation methodology, block adaptive filtering methodology, for the FPD electronic system board which is enclosed by mechanical cover.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1249-1254
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• 2006

Existing adaptive observers may cause the parameter drifts due to disturbances even if state estimation errors remain small. To avoid the drift phenomena in the presence of bounded disturbances, several robust adaptive observers have been introduced addressing bounds in state and parameter estimates. However, it is not easy for these observers to manipulate the size of the bounds with the selection of the observer gain. In order to reduce estimation errors, this paper introduces the (equation omitted) gain minimization problem in the adaptive observer structure, which minimizes the (equation omitted) gain between disturbances and estimation errors. The stability condition of the adaptive observer is reformulated as a linear matrix inequality, and the observer gain is optimally chosen by solving the convex optimization problem. The estimation performance is demonstrated through a numerical example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.108-121
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• 2019

This paper presents the study results on the design of the correction filter to improve the azimuth error estimation of the high-speed guided missile launched from the warship after the transfer alignment. We theoretically proved that the transfer alignment performance is determined by the accuracy of the marine inertial navigation system and the observability of the attitude error state variable in the transfer alignment filter, and that most of navigation errors in high-speed guided missile are caused by azimuth error. In order to improve the azimuth estimation performance of the correction filter, the multiple adaptive estimation method and the adaptive filters adapting the measurement noise covariance or the process noise covariance are proposed. The azimuth estimation performance of the proposed adaptive filter and the existing Kalman filter are compared and analyzed each other for 8 different transfer alignment accuracy cases. As a result of comparison and analysis, it was confirmed that the adaptive filter adapting the process noise covariance has the best azimuth estimation performance. These results can be applied to the design of correction filters for high-speed guided missile.

• Journal of Advanced Information Technology and Convergence
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• v.6 no.1
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• pp.45-57
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• 2016

This paper proposes an adaptive channel estimation scheme for OFDM-based IEEE 802.11ad wireless local area network (WLAN). The standard supports two types of information of OFDM packets for estimating the communication channels, which are the channel estimation field (CEF) of preamble and pilot subcarriers. The CEF-based channel estimation provides better BER (bit error rate) performance at slow fading channel state, whereas the pilot-based channel estimation is good at fast fading channel state. Hence, a combined channel estimation method is introduced to improve the performance. The prediction of the channel state to select the proper channel estimation method is required. In this work, an adaptive channel estimation scheme is also proposed to improve the performance of channel estimation (CE). Basing on a channel quality indicator (CQI), the proper channel estimation method corresponding to the channel type is decided.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.33-39
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• 2019

We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.68-75
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• 2004

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect adaptive fuzzy control.