• 융합신호처리학회논문지
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• 제3권2호
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• pp.30-36
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• 2002

본 논문에서는 선형적응필터를 사용하고 있는 기존의 적응잡음제거 기 의 단점을 보완하기 위해 신경망 적응필터를 이용한 비선형 적응잡음제거기를 다루고 있다. 제안된 적응잡음제거기는 광대역 시변 잡음신호를 사용하여 잡음제거 성능을 조사하였으며 상대평가를 위해 TDL (tapped-delay -line) 선형필터의 적응잡음제거기와 비교하였다. 실험결과에 의하면 적응잡음 제거기의 주입력에 포함된 잡음과 기준입력 사이에 비선형적인 상관관계가 존재하는 경우 신경망 적응잡음제거기는 평균자승오차값을 기준으로 선형잡음제거기보다 더 우수한 성능을 보여주었으며, 또한 리커런트 신경망 적응필터가 순방향 신경망 필터보다 성능이 우수하였다. 따라서 적응잡음제거기에서 광대역 시변잡음을 제거하는데 신경망 적응필터가 선형 적응필터보다 효과적임을 확인하였다.

• 한국자동차공학회논문집
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• 제20권6호
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• pp.126-131
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• 2012

Tire force is one of important parameters which determine vehicle dynamics. However, it is hard to measure tire force directly through sensors. Not only the sensor is expensive but also installation of sensors on harsh environments is difficult. Therefore, estimation algorithms based on vehicle dynamic models are introduced to estimate the tire forces indirectly. In this paper, an estimation system for estimating lateral force and states is suggested. The state-space equation is constructed based on the 3-DOF bicycle model. Extended Kalman Filter, Unscented Kalman Filter and Ensemble Kalman Filter are used for estimating states on the nonlinear system. Performance of each algorithm is evaluated in terms of RMSE (Root Mean Square Error) and maximum error.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• 대한전자공학회논문지SP
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• 제42권6호
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• pp.83-88
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• 2005

본 논문에서는 적외선 영상의 단측형 충격잡음 제거를 위해, 비선형 위치 추정기를 근간으로 하는 충격잡음 검출기를 설계하여 단측형 충격잡음을 검출하고, 검출된 정보를 기반으로 국부윈도우 크기를 적응적으로 가변시켜 중앙값 필터링을 수행하는 비선형 필터를 제안하였다. 가시광 영상에 대해 성능이 입증된 기존 12종 필터와 성능비교를 수행하였다. 정성적 측면에선 제안된 필터가 잡음오염이 과다한 $20\%$ 수준까지도 충분한 잡음제거 성능과 함께 영상의 세부정보를 잘 보존하는 것을 확인할 수 있었다. 정량적 측면에선 PSNR을 측정 비교하였는데, 영상 세부 정보 보존이 우수한 중앙값 필터($3{\times}3$) 보다 13-31[dB] 더 개선된 성능을 얻었으며, 잡음제거 특성이 우수한 중앙값 필터($5{\times}5$) 보다는 18 - 25[dB] 더 개선된 잡음제거 성능을 보였다.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.682-687
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• 2013

Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 추계학술대회 논문집
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• pp.97-101
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• 2001

Recently, as the development of industry, the nonlinear load becomes increased. Because of nonlinear load, the variation of source voltage is generated by the impedace of source side flowed harmonic currents. For blocking harmonic currents by nonlinear load, a series active power filter operates blocking resistance of harmonic currents. The value of blocking resistance shows ideal compensating characteristic out of theoretically infinite value. But the blocking resistance is limited by the problem of the system stability and the capacity of inverter. In this paper, the value of optimum blocking resistance is found by a simulation in the applied system. In the case of unbalanced source voltages, each relation of the blocking resistance is shown. It is proved that blocking resistance of series active power filter relates to a passive filter.

• 전력전자학회논문지
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• 제5권4호
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• pp.403-408
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• 2000

본 논문애서는 비선형부하에서 발생하는 고조파 문제와 역률 저하 문제의 해결을 위한 능동필터를 제연하었다. 인버터와 수동필터로 구성된 능동전력필터 비선형부하에 병렬로 위치하고 전압제어방식으로 동작된다. 제안된 전압제어방식은 기존의 전류제어행 방식에 비해 입럭전압 변동에 강인한 특성을 갖는다. 능통전력필터의 작용으로 부하에 필요한 유효전력은 상용전원에서 공급되며 능동진력필터는 무효전력을 공급하에 입력 역률을 개선하­였다. 또한 부하전압을 정현적으로 유지함ㅇ 따라서 부하전압, 입럭전류 고조파 성분이 저감되있다. 본 논문에서 전압제어용 제어기의 구조를 딘순화하여 전체 시스템의 안정성을 높였다. 다수의 시뮬레이션과 실제 실험을 통하여 제안된 제안된 방식의 타당성을 검증하였다.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.807-810
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• 2015

In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 학술대회
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.77.3-77
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• 2001

An extended robust H$\infty$ filter is proposed for a nonlinear uncertain system. We also analyze the characteristics of the proposed filter such as an H$\infty$ performance criterion using the Lyapunov function method. The analysis results show that proposed filter has a robustness against disturbances such as process and measurement noises and against parameter uncertainties. Then the in-flight alignment for a strapdown inertial navigation system is designed using the presented filter. Simulation results show that the proposed filter effectively improve the performance.