• 제목/요약/키워드: Iterative Learning Control

검색결과 163건 처리시간 0.035초

대규모 시스템에서의 학습제어 알고리즘 (Learning Control Algorithm Applying to Large Scale System)

  • 황동환;변증남;오상록
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1989년도 하계종합학술대회 논문집
    • /
    • pp.112-115
    • /
    • 1989
  • This paper proposes a learning control algorithm for trajectory tracking of large scale system. The controller using only localized informations is composed of stabilizing controller and iterative learning controller. Stabilization and convergence of each subsystem is assured under some conditions which are inequalities of inter-connection terms and learning controller gain.

  • PDF

Play-Back 서보 시스템의 학습제어 방법 (An Iterative Learning Control of Play-Back Servo Systems)

  • 김광배;안현식;오상록;고명삼
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1989년도 추계학술대회 논문집 학회본부
    • /
    • pp.367-371
    • /
    • 1989
  • As a menas of designing a robust servo system for electrical motor drive system, an iterative learning control method is proposed by employing the structure of the model algorithmic control. A sufficient condition for the convergency is shown, and via simulation for permanent magnet synchronous motor drive system, it is demonstrated 1hat the method yields a 'good performance even in the presence of the external load distrurbances.

  • PDF

Improvement of trajectory tracking control performance by using ILC

  • Le, Dang-Khanh;Nam, Taek-Kun
    • Journal of Advanced Marine Engineering and Technology
    • /
    • 제38권10호
    • /
    • pp.1281-1286
    • /
    • 2014
  • This paper presents an iterative learning control (ILC) approach for tracking problems with specified data points that are desired points at certain time instants. To design ILC systems for such problems, unlike traditional ILC approaches, an algorithm which updates not only the control signal but also the reference trajectory at each trial will be developed. The relationship between the reference trajectory and ILC control in tracking problems where there are specified data points through which the system should pass is investigated as the rate of convergence. In traditional ILC, the desired data is stored in a tracking profile file. Due to the huge size of the data file containing the target points, it is important to reduce the computational cost. Finally, simulation results of the presented technique are mentioned and compared to other related works to confirm the effectiveness of proposed scheme.

이산 선형 비최소위상 시스템을 위한 반복 학습 제어의 수렴조건에 대한 연구 (A Study on the Convergence Condition of ILC for Linear Discrete Time Nonminimum Phase Systems)

  • 배성한;안현식;정구민
    • 전기학회논문지
    • /
    • 제57권1호
    • /
    • pp.117-120
    • /
    • 2008
  • This paper investigates the convergence condition of ADILC(iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

이산 선형 시스템에 대한 반복 학습 제어의 수렴성에 대한 연구 (On the Convergence of ILC for Linear Discrete Time Nonminimum Phase Systems)

  • 정구민;안현식
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
    • /
    • pp.225-227
    • /
    • 2006
  • This note investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

  • PDF

불확실한 로봇 시스템을 위한 적응 반복 학습 제어 및 식별 (An Adaptive Iterative Learning Control and Identification for Uncertain Robotic Systems)

  • 최준영
    • 제어로봇시스템학회논문지
    • /
    • 제10권5호
    • /
    • pp.395-401
    • /
    • 2004
  • We present an AILC(Adaptive Iterative Learning Control) scheme and a sufficient condition for system parameter identification for uncertain robotic systems that perform the same tasks repetitively. It is guaranteed that the joint velocity and position asymptotically converge to the reference joint velocity and position, respectively. In addition, it is proved that a sufficient condition for parameter identification is the PE(Persistent Excitation) condition on the regressor matrix evaluated at the reference trajectory during the operation period. Since the regressor matrix on the reference trajectory can be easily computed prior to the real robot operation, the proposed algorithm provides a useful method to verify whether the parameter error converges to zero or not.

반복학습에 의한 MIMO Nonminimum Phase 자율주행 System의 Feedforward 입력신호 생성에 관한 연구 (Feedforward Input Signal Generation for MIMO Nonminimum Phase Autonomous System Using Iterative Learning Method)

  • 김경수
    • 한국군사과학기술학회지
    • /
    • 제21권2호
    • /
    • pp.204-210
    • /
    • 2018
  • As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

반복학습제어를 기반으로 한 회분공정의 고급제어기법 (Advanced Control Techniques for Batch Processes Based on Iterative Learning Control Methods)

  • 이광순
    • Korean Chemical Engineering Research
    • /
    • 제44권5호
    • /
    • pp.425-434
    • /
    • 2006
  • 석유화학공업으로 대표되는 공정산업의 연속공정들은 지난 20여 년간 모델예측제어를 중심으로 고급제어(APC)기법들이 도입되며 운전성 및 생산성 향상에 많은 진보를 이루었다. 이에 반하여 중합반응기를 비롯한 각종 회분공정에는 APC 기법의 도입이 아직 활발히 이루어지지 않고 있다. 이것은 회분공정의 독특한 문제점을 극복하며 원하는 성능을 보장할 수 있는 방법론이 제시되지 못한 데에 가장 큰 이유가 있다고 할 수 있다. 그러나 최근 이러한 문제점들을 극복할 수 있는 APC 기법들이 반복학습제어(ILC)에 근거하여 개발되며 회분공정 APC 환경에 큰 변화가 일어나고 있다. 본 논문에서는 이들 기법들이 다양한 실제 공정에 활발하게 적용되어 운전을 개선할 수 있기를 기대하며, ILC를 기반으로 한 최근의 회분공정 APC 연구동향을 이론과 실례를 통해 소개한다.

주파수 영역에서 반복 학습 제어의 수렴 조건 (Convergence Conditions of Iterative Learning Control in the Frequency Domain)

  • 도태용;문정호
    • 한국지능시스템학회논문지
    • /
    • 제13권2호
    • /
    • pp.175-179
    • /
    • 2003
  • 반복 학습 제어에서 수렴 조건은 수렴 속도와 잔존 오차와 같은 성능을 결정한다. 따라서, 덜 신중한 수렴 조건을 구할 수 있다면, 그 성능은 향상될 것이고 사용 적합한 학습 제어기의 수는 증가된다. 주파수 영역에서, 연속적인 오차들간의 전달 함수의 $H_{\infty}$ 놈(norm)을 학습 시스템의 수렴성을 조사하기 위해 사용해왔다. 그러나, $H_{\infty}$ 놈을 바탕으로 한 수렴 조건이 단조 수렴성에 대하여 명확한 특성을 가진다하더라도, 특히, 다중 입출력 시스템에서 몇 가지 단점을 가진다. 본 논문에서 는 수렴 조건과 수렴의 단조성간의 관계를 밝힌다. 또한 주파수 영역에서 기존의 수렴 조건을 대신할 수 있는 수정된 수렴 조건을 주파수 영역 리아프노프(Lyapunov) 방정식을 이용하여 구한다.