• Title, Summary, Keyword: Iterative learning control

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Design of robust iterative learning controller for linear plant with initial error and time-delay (초기 오차와 시간 지연을 고려한 선형 플랜트에 대한 강인한 반복 학습 제어기의 설계)

  • 박광현;변증남;황동환
    • 제어로봇시스템학회:학술대회논문집
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    • pp.335-338
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    • 1996
  • In this paper, we are going to design an iterative learning controller with the robust properties for initial error. For this purpose, the PID-type learning law will be considered and the design guide-line will be presented for the selection of the learning gain. Also, we are going to suggest a condition for the convergence of control input for a plant with input delay. Several simulation results are presented, which shows the effectiveness of the proposed algorithms.

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Fuzzy iterative learning controller for dynamic plants (퍼지 반복 학습제어기를 이용한 동적 플랜트 제어)

  • 유학모;이연정
    • 제어로봇시스템학회:학술대회논문집
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    • pp.499-502
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    • 1996
  • In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

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Takagi-Sugeno Fuzzy Model-based Iterative Learning Control Systems: A Two-dimensional System Theory Approach

  • Chu, Jun-Uk;Lee, Yun-Jung
    • 제어로봇시스템학회:학술대회논문집
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    • pp.169.3-169
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    • 2001
  • This paper introduces a new approach to analysis of error convergence for a class of iterative learning control systems. First, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established in the form of T-S fuzzy model. We analysis the error convergence in the sense of induced 2 L -norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative learning controller design problem to guarantee the error convergence can be reduced to linear matrix inequality problems. In comparison with others, our learning algorithm ...

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Iterative learning control based on inverse process model

  • Lee, Kwang-Soon
    • 제어로봇시스템학회:학술대회논문집
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    • pp.539-544
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    • 1992
  • An iterative lear-rung control scheme is newly designed in tile frequency domain. Purposing for batch process control, a generic form of feedback-assisted first-order learning is considered first, and the inverse model-based learning algorithm is derived through convergence analysis in the frequency domain. To enhance the robustness of the proposed scheme, a filtered version is also presented. Performance of the proposed scheme is evaluated through numerical simulations.

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LMI-Based Synthesis of Robust Iterative Learning Controller with Current Feedback for Linear Uncertain Systems

  • Xu, Jianming;Sun, Mingxuan;Yu, Li
    • International Journal of Control, Automation, and Systems
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    • v.6 no.2
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    • pp.171-179
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    • 2008
  • This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

Takagi-Sugeno Fuzzy Model-Based Iterative Learning Control Systems: A Two-Dimensional System Theory Approach (Takagi-Sugeno 퍼지모델에 기반한 반복학습제어 시스템: 이차원 시스템이론을 이용한 접근방법)

  • Chu, Jun-Uk;Lee, Yun-Jung;Park, Bong-Yeol
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.5
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    • pp.385-392
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    • 2002
  • This paper introduces a new approach to analysis of error convergence for a class of iterative teaming control systems. Firstly, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established if the form of T-S fuzzy model. We analyze the error convergence in the sense of induced L$_2$-norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative teaming controller design problem to guarantee the error convergence can be reduced to the linear matrix inequality problem. This method provides a systematic design procedure for iterative teaming controller. A simulation example is given to illustrate the validity of the proposed method.

Design guidelines and convergence bound of lterative learning control system (반복 학습 제어 시스템의 설계 지침 및 수렴 범위)

  • 노철래;정명진
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.1
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    • pp.131-138
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    • 1996
  • In this paper, we consider an iterative learning control system(ILCS) consisting of an iterative learning controller, a feedback controller and a controlled plant in the frequency domain. At first, we review the convergence of ILCS. And we give some design guidelines of the ILCS using a nominal model of the plant. Then we present the structured and the unstructured uncertainty bound which guarantees the convergence of the designed iterative learning controller. In particular, we analyze the relationship between the convergence and the magnitude and phase uncertainties. In order to show the usefulness of the proposed analysis and design guidelines, we present some simulation examples. (author). 13 refs., 5 figs.

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Iterative learning control of robot manipulators (로봇 매니퓰레이터의 반복 학습 제어)

  • 문정호;도태용;정명진
    • 제어로봇시스템학회:학술대회논문집
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    • pp.470-473
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    • 1996
  • This paper presents an iterative learning control scheme for industrial manipulators. Based upon the frequency-domain analysis, the input update law of the learning controller is given together with a sufficient condition for the convergence of the iterative process in the frequency domain. The proposed learning control scheme is structurally simple and computationally efficient since it is independent joint control depending only on locally measured variables and it does not involve the computation of complicated nonlinear manipulator dynamics. Moreover, it is capable of canceling the unmodeled dynamics of the manipulator without even the parametric model. Several important aspects of the learning scheme inherent in the frequency-domain design are discussed and the control performance is demonstrated through computer simulations.

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Position Control of Electro Hydraulic Actuator (EHA) using an Iterative Learning Control (반복 학습제어를 이용한 전기유압액추에이터의 위치제어)

  • Nam, D.N.C.;Tri, N.M.;Park, H.G.;Ahn, K.K.
    • Journal of Drive and Control
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    • v.11 no.4
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    • pp.1-7
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    • 2014
  • This paper presents the development of a compact position generator to be used for industrial purposes based on a pump controlled Electro-Hydraulic Actuator (EHA), which is closed-loop controlled by an embedded based Iterative PID controller. The controller is designed by combining the PID controller and the iterative learning scheme to perform tracking control for periodically desired references. Control algorithm is implemented on an embedded computer (AD 7011-EVA) which makes the implementation and application in industrial environments easier.

Control of a batch reactor using iterative learning (반복학습을 이용한 회분식 반응기의 제어)

  • 조문기;방성호;조진원;이광순
    • 제어로봇시스템학회:학술대회논문집
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    • pp.81-86
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    • 1991
  • The iterative learning operation has been utilized in the temperature Control of a batch reactor. A generic form of feedback-assisted first-order learning control scheme was constructed and then various design and operation modes were derived through convergence and robustness analysis in the frequency domain. The proposed learning control scheme was then implemented on a bench scale batch reactor with the heat of reaction simulated by an electric heater. The results show a great improvement in the performance of control as the number of batch operations progressed.

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