• Title, Summary, Keyword: Generalized predictive control

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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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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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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.

Position Control of Induction Motor Using Generalized Predictive Control (일반형 예측제어을 이용한 유도전동기의 위치제어)

  • Na, Jae-Du;Kim, Sang-Uk;Kim, Young-Seok
    • Proceedings of the KIEE Conference
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    • pp.340-343
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    • 1995
  • This paper consists of the position control of induction motor using Generalized Predictive Control. Full order flux observer is also used for the purpose of estimating rotor fluxes. By using Generalized Predictive Control algorithm, the improved position control is realized in this paper. The proposed control method has been implemented by a 32 bit floating point TMS320C31 DSP chip.

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Implementation and tuning of adaptive generalized predictive PID for process control (공정 제어를 위한 적응 GP-PID의 구현과 동조)

  • Lee, Chang-Gu;Seol, O-Nam;Kim, Seong-Jung
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.2
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    • pp.197-203
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    • 1997
  • In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

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Fuzzy Neural Network Based Generalized Predictive Control of Chaotic Nonlinear Systems (혼돈 비선형 시스템의 퍼지 신경 회로망 기반 일반형 예측 제어)

  • Park, Jong-Tae;Park, Yoon-Ho
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.2
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    • pp.65-75
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    • 2004
  • This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.

Accurate Position Control of Hydraulic Motor Using NNGPC (NNGPC를 이용한 유압모터의 고정도 위치제어)

  • 박동재;안경관;이수한
    • 제어로봇시스템학회:학술대회논문집
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    • pp.143-143
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    • 2000
  • A neural net based generalized predictive control(NNGPC) is presented for a hydraulic servo position control system. The proposed scheme employs generalized predictive control, where the future output being generated from the output of artificial neural networks. The proposed NNGPC does not require an accurate mathematical model for the nonlinear hydraulic system and takes less calculation time than GPC algorithm if the teaming of neural network is done. Simulation studies have been conducted on the position control of a hydraulic motor to validate and illustrate the proposed method.

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Generalized predictive control with exponential weight to control tempera-tures in ceramic drying furnace (세라믹 건조로 온도 제어를 위한 가중계수를 갖는 일반형 예측제어)

  • 임태규;성원준;금영탁;송창섭
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.13 no.6
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    • pp.284-289
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    • 2003
  • The electric furnace, inside which the desired temperature is kept by the generated heat, is known to be a difficult system to control and model exactly because system parameters and response delayed time are varied as the temperature and positions are changed. In this study, the GPCEW (generalized predictive control with exponential weight), which always guarantees the stability of the closed loop system and can be effectively applied to the internally unstable system, was introduced to the ceramic drying electric furnace and was verified by showing its temperature tracking performance experimentally.

Design of a generalized predictive controller for nonlinear plants using a fuzzy predictor (퍼지 예측기를 이용한 비선형 일반 예측 제어기의 설계)

  • Ahn, Sang-Cheol;Kim, Yong-Ho;Kwon, Wook-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.272-279
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    • 1997
  • In this paper, a fuzzy generalized predictive control (FGPC) for non-linear plants is proposed. In the proposed method, the receding horizon control is applied to the control part, while fuzzy systems are used for the predictor part. It is suggested that the fuzzy predictor is time-varying affine with respect to input variables for easy computation of control inputs. Since the receding horizon control can be obtained only with a predictor instead of a plant model, the fuzzy predictor is obtained directly from input-output data without identifying a plant model. A parameter estimation algorithm is used for identifying the fuzzy predictor. The control inputs of the FGPC are computed by minimizing a receding horizon cost function with predicted plant outputs. The proposed controller has a similar architecture to the generalized predictive control (GPC) except for the predictor synthesis method, and thus may possess inherent good properties of the GPC. Computer simulations show that the performance of the FGPC is satisfactory.

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Receding horizon predictive controls and generalized predictive controls with their equivalance and stability

  • Kwon, Wook-Hyun;Lee, Young-Il
    • 제어로봇시스템학회:학술대회논문집
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    • pp.49-55
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    • 1992
  • In this paper, we developed a Receding Horizon Predictive Control for Stochastic state space models(RHPCS). RHPCS was designed to minimize a quadratic cost function. RHPCS consists of Receding Horizon Tracking Control(RHTC) and a state observer. It was shown that RHPCS is equivalent to Generalized Predictive Control(GPC) when the underlying state space model is equivalent to the I/O model used in the design of GPC. The equivalence between GPC and RHPCS was shown through. the comparison of the transfer functions of the two controllers. RHPCS provides a time-invarient optimal control law for systems for which GPC can not be used. The stability properties of RHPCS was derived. From the GPC's equivalence to RHPCS, the stability properties of GPC were shown to be the same as those for RHTC.

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