• Journal of Power Electronics
• /
• 제9권3호
• /
• pp.403-409
• /
• 2009

Automatically tuned passive filters can improve power quality to a great extent in power systems. A novel three-phase shunt auto-tuned filter is designed to effectively compensate source current harmonics and to provide reactive power required by the non-linear load, which draws a highly reactive, harmonic-rich current from the supply. An artificial neural network (ANN) based controller selects filter component values in accordance with reactive power requirement and harmonic compensation. Traditional passive filters are permanently connected to the system and draw large amounts of source current even under light load conditions. By using auto-tuned filters, the passive filter components can be controlled according to load variations and, hence, draw only required source currents. The selection is done by the ANN with the help of a properly tuned knowledge base to provide instantaneous compensation using a digital controller.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.15-17
• /
• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.502-504
• /
• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of FIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate FIR filter parameter using the genetic algorithm.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2008년도 하계종합학술대회
• /
• pp.547-548
• /
• 2008

Linearity improvement technique of transconductor is presented in the paper. In order to certify the linearity improvement of proposed transconductor, the 3rd-order Elliptic low-pass Gm-C filter which provides 5MHz cutoff is implemented by using the transconductor. According to the IIP3 measurement result of filters, proposed filter has higher IIP3 than normal source-degeneration filter; the In-band IIP3 of proposed and normal filter are 10.1 dBm and 7.5 dBm respectively. The filter is fabricated in 1P6M $0.18-{\mu}m$ CMOS while consuming the 3.3mW with 1.8 Vdd. The in-band input-referred noise voltage is $62.3{\mu}Vrms$ and the SFDR is 54.1 dB.

• 한국컴퓨터정보학회논문지
• /
• 제7권2호
• /
• pp.68-72
• /
• 2002

본 논문에서는 OTA의 원리와 기본응용에 대하여 연구하였다. 또한 OTA를 응용하여 3개의 입력과 1개의 출력을 갖는 2차 필터를 설계하여 3입력중의 각각 1입력만을 사용한다면 각각 저역통과, 중역통과, 고역통과 필터의 특성을 얻을 수 있었다. 컴퓨터 시뮬레이션 결과 이론값과 잘 일치하였으며, 이 필터는 저왜곡, 고주파 특성을 갖는 통신 시스템의 응용에 사용될수 있다.

• Smart Structures and Systems
• /
• 제25권1호
• /
• pp.37-45
• /
• 2020

This paper aims at enlightening the properties, computational and implementation issues related to Kalman filter based state estimation algorithms and sliding mode observers, by applying them for estimating the states of a smart structure system. The Kalman based estimators considered in this work are Kalman filter and information filter and, the sliding mode observers considered are Utkin observer and higher order sliding mode observer. A fourth order linear time invariant model of a piezo actuated beam is used in this work. This structure is embedded with four number of piezo patches, of which two act as sensors, one as disturbance actuator and the other as control actuator. The performance of the state estimation algorithms is evaluated through simulation, for the first two vibrating modes of the piezo actuated structure, when the structure is maintained at first mode and second mode resonance.

• 한국철도학회논문집
• /
• 제7권3호
• /
• pp.173-179
• /
• 2004

This paper describes a low-cost single-phase active power filter, which consists of a half-bridge PWM inverter with a simple control circuit. In order to verify the performance of proposed active power filter, many computer simulations with EMTP codes and experimental works with a hardware prototype were done. Both results confirm that the proposed active power filter shows excellent performance to eliminate the harmonics generated in the single-phase non-linear load. The active power filter has advantage of low implementation cost and compact size, using a half-bridge inverter and a simple control circuit with only one current sensor. So, it can be fabricated as a plug-in type. This paper shows the necessity and a good possibility to apply such advantage to the electric railway system.

• International Journal of Aeronautical and Space Sciences
• /
• 제18권3호
• /
• pp.535-544
• /
• 2017

In-flight aircraft engine performance estimation is one of the key techniques for advanced intelligent engine control and in-flight fault detection, isolation and accommodation. This paper detailed the current performance degradation estimation methods, and an improved hybrid Kalman filter via velocity-based LPV (VLPV) framework for these needs is proposed in this paper. Composed of a nonlinear on-board model (NOBM) and VLPV, the filter shows a hybrid architecture. The outputs of NOBM are used for the baseline of the VLPV Kalman filter, while the system performance degradation factors on-line estimated by the measured real system output deviations are fed back to the NOBM for its updating. In addition, the setting of the process and measurement noise covariance matrices' values are also discussed. By applying it to a commercial turbofan engine, simulation results show the efficiency.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.978-983
• /
• 2003

In this paper, we propose a fault detection method for extended Kalman filter in decentralized filter structure. To detect a fault, a consistency between filter output and a monitoring signal is tested. State propagators are used to obtain the monitoring signal. However, the output of state propagator increases in magnitude and finally diverges as time runs. To solve such problem, two-propagator method was proposed for linear system. Two propagators are reset by Kalman filter output, alternatively, to avoid divergence. But a test statistics change abruptly at the reset instant in that method. Hence a N-step propagator method is proposed to fix up the problem. In the N-step propagator, only time propagations are performed from k-N+1 step to k step without measurement updates. A test statistics are defined by errors and its covariance between extended Kalman filter and N-step propagator. These fault detection methods are applied to integrated strapdown inertial navigation system (SDINS). By computer simulation, it is shown that the proposed methods detect a fault effectively.

• 제어로봇시스템학회논문지
• /
• 제20권9호
• /
• pp.930-935
• /
• 2014

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.