• Title/Summary/Keyword: Adaptive power control

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An Edge-Based Algorithm for Discontinuity Adaptive Image Smoothing (에지기반의 불연속 경계적응 영상 평활화 알고리즘)

  • 강동중;권인소
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.273-273
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    • 2000
  • We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

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MRAC Fuzzy Control for High Performance of Induction Motor Drive (유도전동기 드라이브의 고성능 제어를 위한 MRAC 퍼지제어)

  • 정동화;이정철
    • The Transactions of the Korean Institute of Power Electronics
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    • v.7 no.3
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    • pp.215-223
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    • 2002
  • This paper investigates the adaptive control of a fuzzy logic based speed and flux controller fur a vector controlled induction motor drive. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the model reference adaptive control(MRAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the Proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

Implementation of a Robust Fuzzy Adaptive Speed Tracking Control System for Permanent Magnet Synchronous Motors

  • Jung, Jin-Woo;Choi, Han Ho;Lee, Dong-Myung
    • Journal of Power Electronics
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    • v.12 no.6
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    • pp.904-911
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    • 2012
  • This paper presents a fuzzy adaptive speed controller that guarantees a fast dynamic behavior and a precise trajectory tracking capability for surfaced-mounted permanent magnet synchronous motors (SPMSMs). The proposed fuzzy adaptive control strategy is simple and easy to implement. In addition, the proposed speed controller is very robust to system parameter and load torque variations because it does not require any accurate parameter values. The global stability of the proposed control system is analytically verified. To evaluate the proposed fuzzy adaptive speed controller, both simulation and experimental results are shown under motor parameter and load torque variations on a prototype SPMSM drive system.

Position Control of an Electro Hydraulic Actuator Using Adaptive Control Method (적응제어 기법을 이용한 전기-유압 액츄에이터의 위치제어)

  • Cho, S.H.
    • Transactions of The Korea Fluid Power Systems Society
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    • v.7 no.3
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    • pp.1-6
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    • 2010
  • This paper deals with the issue of simple adaptive position control for a pump-controlled cylinder system. A fixed displacement pump is utilized instead of servo valve and its speed is controlled by AC motor. The whole control system is composed of a pair of interconnected subsystems, that is, a feedback control system and a feedforward control system. From experiments it is shown that position control using simple adaptive control can accomplish significant reduction in position tracking error comparing to a conventional PID control.

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Adaptive control of time varying system (시변시스템의 적응제어에 관한 연구)

  • 곽유식;양해원
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.264-267
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    • 1988
  • One of the major reasons of Adaptive Control is to control time varying systems. In this paper new adaptive algorithms are suggested for a class of linear time varying systems that satisfy certain assumptions. These algorithms consist of three modules, modeling, parameter estimation and control. The key feature of this paper is that power series of time varying parameters are used for estimation.

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An Advanced Three-Phase Active Power Filter with Adaptive Neural Network Based Harmonic Current Detection Scheme

  • Rukonuzzaman, M.;Nakaoka, Mutsuo
    • Journal of Power Electronics
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    • v.2 no.1
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    • pp.1-10
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    • 2002
  • An advanced active power filter for the compensation of instantaneous harmonic current components in nonlinear current load is presented in this paper. A novel signal processing technique using an adaptive neural network algorithm is applied for the detection of harmonic components generated by three-phase nonlinear current loads and this method can efficiently determine the instantaneous harmonic components in real time. The control strategy of the switching signals to compensate current harmonics of the three-phase inverter is also discussed and its switching signals are generated with the space voltage vector modulation scheme. The validity of this active filtering processing system to compensate current harmonics is substantiated on the basis of simulation results.

LED Driver Solution for Backlighting large TFT-LCD Panels with Adaptive Power Control & Video Synchronization

  • Dhayagude, Tushar;Dilip, S;Santo, Hendrik;Vi, Kien;Chen, Sean;Kim, Min-Jong;Schindler, Matt;Ghoman, Ran
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.1487-1490
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    • 2008
  • mSilica developed a scalable integrated circuit solution for driving multiple arrays of LEDs to backlight TFT-LCD panels. The drivers incorporate adaptive power control of the DC-DC power supply powering the LEDs to improve the efficiency while synchronizing PWM dimming with video timing signals VSYNC and HSYNC to reduce motion blur.

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Development of active noise control system for quieting transformer noise (변압기 주위소음 정음화 시스템 개발)

  • 최효열
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1360-1363
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    • 1997
  • Development and realizatioin of adaptive Active Noise Cntrol used for quieting transformer nosie are planed to provide workers with comfortable working environment and to attenuate the noise for residents in many noisy areas(power plant, power transformer, GIS transformer etc.).

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Design of an Adaptive Neurofuzzy-Based Power System Stabilizer (적응 뉴로 퍼지 전력계통 안정화 장치의 설계)

  • Jeong, Hyeong-Hwan;Jeong, Mun-Gyu;Kim, Sang-Hyo
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.11
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    • pp.497-505
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    • 2001
  • The power system stabilizer(PSS) is important for the suppression of low-frequency oscillation and the improvement of system stability. In this paper, An Adaptive Neurofuzzy-based Power System Stabilizer(ANF PSS) is proposed as the new PSS type. The proposed PSS employs a multi-layer adaptive network. The network is trained directly from the input and the output of the generating unit. The algorithm combines the advantages of the Artificial Neural Network(ANN) and Fuzzy Logic Control(FLC) schemes. Studies show that the proposed ANF PSS can provide good damping of the power system over the wide range of operating conditions and improve the dynamic performance of the system.

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Adaptive Variable Angle Control in Switched Reluctance Motor Drives for Electric Vehicle Applications

  • Cheng, He;Chen, Hao;Xu, Shaohui;Yang, Shunyao
    • Journal of Power Electronics
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    • v.17 no.6
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    • pp.1512-1522
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    • 2017
  • Switched reluctance motor (SRM) is suitable for electric vehicle (EV) applications with the advantages of simple structure, good overload capability, and inherent fault-tolerance performance. The SRM dynamic simulation model is built based on torque, voltage, and flux linkage equations. The EV model is built on the basis of the analysis of forces acting on a vehicle. The entire speed range of the SRM drive is then divided into constant torque and constant power areas. The command torque of the motor drive system is given according to the accelerator pedal coefficient and motor operation areas. A novel adaptive variable angle control is proposed to avoid the switching chattering between the current chopping control and angle position control modes in SRM drives for EV applications. Finally, simulation analysis and experimental results are conducted to verify the accuracy of the proposed simulation model and control strategy.