• Title, Summary, Keyword: Predictive Control

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The Design of Trajectory Controller using Neural Networks Simulating Predictive Control Method for Mobile Robot (이동로봇의 예측제어방법을 모사한 신경회로망 궤적제어기 설계)

  • Park, Jin-Hyun;Lee, Tae-Hwan;Bae, Jun-Kyung
    • Journal of the Korean Society of Mechanical Technology
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    • v.19 no.4
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    • pp.538-544
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    • 2017
  • The predictive control system using model-based predictive control is a very effective way to optimize the present inputs considering the states and future errors of the reference trajectory, but it has a drawback in that a control input matrix must be repeatedly calculated with a long calculation time at every sampling for minimizing future errors in a predictive interval. In this study, we applied the neural network simulating the predictive control method for the trajectory tracking control of the mobile robot to reduce complex control method and computation time which are the disadvantage of predictive control. In addition, the neural network showed excellent performance by the generalization even for a different reference trajectory. Therefore, The controller is designed by modeling the model-based predictive control gains for the reference trajectory using a neural networks. Through the computer simulation, the proposed control method showed better performance than the general predictive control method.

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

  • Park, Juong-Il;Chung, Jong-Dae;Park, Keh-Kun
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.9
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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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A Study on Anti-Sway of Crane using Neural Network Predictive PID Controller (Anti-Sway에 관한 연구)

  • 손동섭;이진우;민정탁;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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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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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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    • 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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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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    • 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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    • v.5 no.1
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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.

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

  • Cho, Sung-Hwan;Hong, Seong-Ki
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.27 no.4
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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.

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

  • Oh, Sea-Cheon;Yeo, Yeong-Koo
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.4
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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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Bilinear mode predictive control methods for chemical processes

  • Yeo, Yeong-Koo;Oh, Sea Cheon;Williams, Dennis C.
    • ICROS
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    • v.2 no.1
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    • pp.59-71
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    • 1996
  • In the last decade, the model predictive control methods have enjoyed many industrial applications with successful results. Although the general predictive control methods for nonlinear chemical processes are not yet formulated, the promising features of the model predictive control methods attract attentions of many researchers who are involved with difficult but important nonlinear process control problems. Recently, the class of bilinear model has been introduced as an useful tool for examining many nonlinear phenomena. Since their structural properties are similar to those of linear models, it is not difficult to develop a robust adaptive model predictive control method based on bilinear model. We expect that the model predictive control method based on bilinear model will expand its region in the world of nonlinear systems.

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