• 제목/요약/키워드: predictive control

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Controls Methods Review of Single-Phase Boost PFC Converter : Average Current Mode Control, Predictive Current Mode Control, and Model Based Predictive Current Control

  • Hyeon-Joon Ko;Yeong-Jun Choi
    • 한국컴퓨터정보학회논문지
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    • 제28권12호
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    • pp.231-238
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    • 2023
  • 부스트 PFC (Power Factor Correction)컨버터는 AC 입력 전류의 단일 역률과 낮은 THD (Total Harmonic Distortion)를 달성하기 위해 다양한 제어기법들이 연구되고 있다. 그중 인덕터 전류의 평균값을 전류지령에 추종하도록 제어하는 평균전류 모드 제어가 있으며 가장 널리 사용되고 있다. 하지만, 오늘날 디지털 프로세서의 발달로 고도화된 디지털 제어가 가능해지면서 부스트 PFC 컨버터의 예측제어가 관심을 받고 있다. 예측제어에는 예측 알고리즘으로 듀티를 미리 생성하는 예측전류 모드 제어 및 모델을 기반으로 한 비용함수를 선정하여 스위칭 동작을 하는 모델예측제어로 분류된다. 따라서 본 논문에서는 부스트 PFC 컨버터의 평균전류 모드 제어, 예측전류 모드 제어, 모델예측 전류 제어를 간단히 설명한다. 또한, 시뮬레이션을 통해 전체 부하 및 다양한 외란 조건에서의 전류 제어를 비교 분석한다.

Predictive Spacecraft Attitude Control under External Disturbances

  • Sam, Myung-Hyun;Suk, Oh-Choong;Choong, Bang-Hyo;Jea, Tahk-Min
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.62.3-62
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    • 2001
  • The predictive control is one of the nonlinear three-axis rotation methods. The desired trace of a satellite is pre-determined, and the control inputs are designed so that the satellite follows the ´predictive´ trace. The predictive control has been adapted to the research for the three-axis attitude control. In that case, the control variables are the quaternion represented the angular rates and attitude angles of the body about the three-axes. The objective of this paper is to propose to design a predictive controller for the three-axis attitude control under external disturbances. In order to do that, this paper proposes how to construct a predictive control law including disturbances and to discern them. The basic algorithm of the existent predictive control is partially modified, and the presumption and modeling of disturbances are performed ...

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Mean Horizon 제어방식을 사용한 일반화 예측 자기동조 제어 (A Generalized Predictive Self-Tuning Control Using Mean Horizon Control Method)

  • Park, Juong-Il;Chung, Jong-Dae;Park, Keh-Kun
    • 대한전자공학회논문지
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    • 제25권9호
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    • pp.1039-1045
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    • 1988
  • In the original incremental generalized predictive control, the receding horizon predictive control is introduced as a control law. But in this paper, we propose a generalized predictive self-tuning control using full-valued incremental controls. The control law is a mean horizon predictive control. The effectiveness of this algorithm in a variable time delay or load disturbances environment is demonstrated by computer simulation. The controlled plant is a nonminimum phase system.

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The PID Controller for Predictive control Algorithm

  • Kim, Sang-Joo;Seo, Sang-Wook;Kim, Gi-Du;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.608-613
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    • 2004
  • This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.

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Anti-Sway에 관한 연구 (A Study on Anti-Sway of Crane using Neural Network Predictive PID Controller)

  • 손동섭;이진우;민정탁;이권순
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2002년도 춘계학술대회논문집
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    • pp.219-227
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    • 2002
  • In this paper, we designed neural network predictive PID controller to control sway happened in transfer of trolley for automatic travel control system. We include dynamic character of nonlinear system, and mathematical expression veny simple used neural network. When various establishment location and surrounding disturbance were approved based on mathematical modelling of crane, controller designed to become effective control location error and vibration angle of two control variables that simultaneously can predictive control. Neural network predictive PID controller produced parameter of PID controller using neural network self-tuner. Neural network self-tuner's input used crane's output and neural network predictive output. Neural network self-tuner using error back propagation algorithm. We analyzed control performance comparison through computer simulation when applied disturbance about sway of location and angle in transfer of crane. The results show that the proposed neural network predictive PID controller has better performances than general PID controller, neural network PID controller.

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A Nash Solution to Predictive Control Problem for a Class of Nonlinear Systems

  • Ahn, Choon-Ki;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.76.5-76
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    • 2002
  • In this paper, we provide a Nash solution to predictive control problem for nonminimum phase singular nonlinear systems. Until now, there is no result on predictive control problem for this class of nonlinear systems. Chen's recent work considered predictive control problem for a class of nonlinear systems with ill-defined relative degree. Since his work is not a result considered in the feedback linearization framework, there is no a result on singular probem in his paper. In contrast to the existing predictive control result, our work considers two main obstacles (singularity and nonminimum phase) in the feedback linearization framework. For a generally formu...

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Optimal design of the PID Controller using a predictive control method

  • Kim, Sang-Joo;Lee, Jang-Myung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권1호
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    • pp.69-75
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    • 2005
  • This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.

인버터시스템 적용 지역난방 시스템의 2차측 공급수 온도 제어방안에 따른 에너지사용량 실증 비교 (Actual Energy Consumption Analysis of Temperature Control Strategies for Secondary Side Hot Water District Heating System with an Inverter)

  • 조성환;홍성기
    • 설비공학논문집
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    • 제27권4호
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    • pp.179-186
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    • 2015
  • In this study, the actual energy consumption of the secondary side District Heating System (DHS) with different hot water supply temperature control methods is compared. The two methods are Outdoor Temperature Reset Control and Outdoor Temperature Predictive Control. While Outdoor Temperature Reset Control has been widely used for energy savings of the secondary side system, the results show that the Outdoor Temperature Predictive Control method saves more energy. In general, the Outdoor Temperature Predictive Control method lowers the supply temperature of hot water, and it reduces standby losses and increases the overall heat transfer value of heated spaces due to more flow into the space. During actual energy consumption monitoring, the Outdoor Temperature predictive Control method saves about 6.6% of energy when compared to the Outdoor Temperature Reset Control method. Also, it is found that at partial load condition, such as during daytime, the fluctuation of hot water supply temperature with Outdoor Temperature Reset Control is more severe than that with Outdoor Temperature Predictive Control. Thus, it proves that Outdoor Temperature Predictive Control is more stable even at partial load conditions.

쌍일차 모델을 이용한 폐열 스팀 보일러의 액위 적응 예측 제어 (Adaptive predictive level control of waste heat steam boiler based on bilinear model)

  • 오세천;여영구
    • 제어로봇시스템학회논문지
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    • 제2권4호
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    • pp.344-350
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    • 1996
  • An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

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위상제어 정류기의 예측전류제어를 위한 새로운 고정밀 게이팅 알고리즘 (High precision Gating Algorithm for Predictive Current Control of Phase Controlled Rectifier)

  • 정세종;송승호
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권3호
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    • pp.206-211
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    • 2004
  • In phase controlled rectifier, it's been known that a fast response is achieved by predictive current control without any overshoot. The frequent sampling period is essential to improve the firing accuracy in conventional predict current control. However, improving the firing accuracy if difficult to reduce the period of sampling efficiently because current sampling and predictive current control is carried out in every period and the ON-OFF current control is performed by comparing two different one. To improve the firing accuracy at the predictive current control, the calculated firing angle is loaded into the high-accuracy hardware timer. So the calculation of exact crossing point between the predictive and actual current is the most important. In this paper, the flow chart for proposed firing angle calculation algorithm is obtained for the fastest current control performance in transient state. The performance of proposed algorithm is verified through simulations and experiments.