• Title/Summary/Keyword: Iterative Learning Control

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A CMAC-based pressure tracking controller design for hydroforming process (CMAC를 이용한 하이드로 포밍 공정의 압력제어기 설계)

  • 이우호;박희재;조형석;현봉섭
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.302-307
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    • 1989
  • A pressure tracking control of hydroforming process is considered in this paper. To account for nonlinearities and uncertainties of the process, an iterative learning control scheme is proposed using Cerebellar Model Arithmatic Computer (CMAC). The experimental result shows that the proposed learning control is superior to any fixed gain controller in the sense that it enables the system to do the same work more effectively as the number of operation increases.

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Extended Direct Learning Control for Single-input Single-output Nonlinear Systems (단일 입출력 비선형 시스템에 대한 확장된 직접학습제어)

  • Park, Joong-Min;Ahn, Hyun-Sik;Kim, Do-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.39 no.5
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    • pp.1-7
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    • 2002
  • In this paper, an extended type of a direct learning control(DLC) method is proposed for the effective control of systems which perform a given task repetitively. DLC methods have been suggested to overcome the defects of iterative learning control, the learning process should be resumed from the beginning even if a slight change occurs in the desired output pattern. If a given desired output trajectory is "proportional" to the output trajectories which are learned previously, we can obtain the desired control input directly without the iterative learning process by using the DLC. First, most existing DLC methods are shown to be applicable only to single-input single-output systems with the relative degree one and then, an extended type of DLC is proposed for a class of nonlinear systems having the relative degree more than or equal to one by using the known relative degree of a nonlinear system. By the simulation results for the arbitrary nonlinear system with the relative degree more than one, the validity and the performance of the proposed DLC method are examined.

Analysis and Design of Jumping Robot System Using the Model Transformation Method

  • Suh Jin-Ho;Yamakita Masaki
    • Journal of Electrical Engineering and Technology
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    • v.1 no.2
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    • pp.200-210
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    • 2006
  • This paper proposes the motion generation method in which the movement of the 3-links leg subsystem in constrained to slider-link and a singular posture can be easily avoided. This method is the realization of jumping control moving in a vertical direction, which mimics a cat's behavior. To consider the movement from the point of the constraint mechanical system, a robotics system for realizing the motion will change its configuration according to the position. The effectiveness of the proposed scheme is illustrated by simulation and experimental results.

Repetitive learning method for trajectory control of robot manipulators using disturbance observer

  • Kim, Bong-Keun;Chung, Wan-Kyun;Youm, Youngil
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.99-102
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    • 1996
  • A novel iterative learning control scheme comprising a unique feedforward learning controller and a disturbance observer is proposed. Disturbance observer compensates disturbance due to parameter variations, mechanical nonlinearities, unmodeled dynamics and external disturbances. The convergence and robustness of the proposed controller is proved by the method based on Lyapunov stability theorem. The results of numerical simulation are shown to verify the effectiveness of the proposed control scheme.

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Direct Learning Control For Linear Feedback Systems

  • Ahn, Hyun-Sik;Park, Ki-Hong;Heo, Seung-Jin
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.96-100
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    • 2003
  • In this paper, a DLC method is proposed for linear feedback systems to improve the tracking performance when the task of the system is repetitive. DLC can generate the desired control input directly from the previously learned control inputs corresponding to other output trajectories. It is assumed that all the desired output functions considered in this paper have some relations called proportionality and it is shown by mathematical analysis that DLC can be utilized to generate additional control efforts for the perfect tracking. To show the validity and tracking performance of the proposed method, some simulations are performed for the tracking control of a linear system with a PI controller.

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Study on Vibration Suppression of 2-Mass Resonant System Using Iterative Learning Control (반복 학습 제어를 이용한 2관성 공진계의 진동 억제에 관한 연구)

  • 이학성
    • Proceedings of the IEEK Conference
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    • 2003.07c
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    • pp.2585-2588
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    • 2003
  • 2 관성 공진계는 마른 응답을 위해 제어이득을 크게 하면 공진에 의해 축비틀림 진동이 일어나는 경우가 많다. 본 논문에서는 반복 학습 제어기법을 활용하여 불확실한 모델 계수를 포함하는 2 관성 공진계의 진동억제를 시도한다. 2관성 공진계의 경우 제어 대상이 되는 부하측 속도는 학습 제어로 직접 적용하기가 힘들고 또한 측정 또한 어렵다. 본 논문에서는 부하측 속도와 전동기측 속도간의 관계를 이용하여 직접 부하측 속도를 제어하는 대신 전동기측 속도를 제어하여 간접적으로 부하측 속도를 제어하였다. 제안된 방식은 전형적인 2 관성 공진계에 모의 실험을 통해 적용되었고, 정확한 모델이 없이도 진동 없는 마른 응답특성을 보여준다.

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Control and Parameter Estimation of Uncertain Robotic Systems by An Iterative Learning Method (불확실한 로보트 시스템의 제어와 파라미터 추정을 위한 반복학습제어기법)

  • Kuc, Tae-Yong;Lee, Jin-Soo
    • Proceedings of the KIEE Conference
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    • 1990.11a
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    • pp.421-424
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    • 1990
  • An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

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Study on Position Control of 2-Mass Resonant System Using Iterative Learning Control (반복 학습 제어를 이용한 2관성 공진계의 위치 제어 관한 연구)

  • 이학성;문승빈
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09b
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    • pp.137-140
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    • 2003
  • 2관성 공진계는 전동기와 부하 사이에 탄성이 있는 동력 전달 체계를 포함하는 시스템으로 고속 제어시 진동이 발생된다. 이와 같은 2관성 공진계에 대해 궁극적인 출력이 되는 부하의 위치 및 속도는 측정하기가 어렵다. 이에 기존의 연구들은 추정기등을 이용하여 부하의 속도를 추정하여 이를 제어에 활용하는 방식으로 구성되어진다. 그러나 이와 같이 추정기를 사용하기 위해서는 정확한 모델이 필요하다. 본 논문에서는 다소 부정확 모델에 대해서도 매우 정교한 제어 성능을 갖는 반복 학습 제어를 이용하여 2관성 공진계의 위치 제어를 시도하고자 한다. 제시된 방법은 2관성 공진계에 대한 모델링이 정확하지 않더라도 진동 없이 정확한 위치 제어가 가능하다.

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Virtual Reference Input Generation Using Direct Learning Control (직접학습제어를 이용한 가상 기준입력 생성)

  • Ahn, Hyun-Sik;Jeong, Gu-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.3
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    • pp.611-614
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    • 2007
  • In this paper, a Direct Learning Control (DLC) method is presented to generate a virtual reference input for linear feedback systems to improve the output tracking performance. The original reference input is effectively modified by the DLC without any iterative learning process. The presented DLC is designed based on the information on the relative degree of a system and previously generated virtual reference inputs. It is illustrated by simulations that the virtual reference input generated by the proposed DLC can achieve high tracking performance, although the reference input cannot be appropriately shaped by using existing DLC methods.

A study on The Real-Time Implementation of Intelligent Control Algorithm for Biped Robot Stable Locomotion (2족 보행로봇의 안정된 걸음걸이를 위한 지능제어 알고리즘의 실시간 실현에 관한 연구)

  • Nguyen, Huu-Cong;Lee, Woo-Song
    • Journal of the Korean Society of Industry Convergence
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    • v.18 no.4
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    • pp.224-230
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    • 2015
  • In this paper, it is presented a learning controller for repetitive walking control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured due to the walking period through the intelligent control, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of intelligent control to biped robotic motion is shown via dynamic simulation with 25-DOF biped walking robot.