• Title/Summary/Keyword: genetic tracking

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A Tracking Vibration Estimation System Using a Genetic Algorithm (유전자 알고리즘을 이용한 트랙킹 진동량 추정 시스템)

  • Jin, Kyoung-Bog;Lee, Moon-Noh
    • Journal of the Semiconductor & Display Technology
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    • v.10 no.2
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    • pp.25-30
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    • 2011
  • This paper presents a tracking vibration estimation system of the track-following system using a tracking loop gain adjustment algorithm and a genetic algorithm. The algorithms are introduced to estimate accurately the tracking vibration quantity in spite of the uncertainties of the tracking actuator. An estimated actuator model can be found by applying a genetic algorithm. Accordingly, the tracking vibration quantity can be estimated from the measured tracking error, the tracking controller and the estimated actuator model. The proposed tracking vibration estimation method is applied to the track-following system of an optical recording device and is evaluated through the experimental result.

An Intelligent Control of Mobile Robot Using Genetic Algorithm (유전자 알고리즘을 이용한 이동로봇의 지능제어)

  • 한성현
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.3
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    • pp.126-132
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    • 2004
  • This paper proposed trajectory tracking control based on genetic algorithm. Trajectory tracking control scheme are real coding genetic algorithm(RCGA) and back-propagation algorithm(BPA). Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studies have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using real coding genetic algorithm and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verity numerical simulations and the results show better performance than constant gain controller.

Design of a Tracking Gain-up Controller for the Vibration Suppression of Tracking Actuator (트랙킹 액추에이터의 진동 억제를 위한 트랙킹 Gain-up 제어기 설계)

  • Lee, Moonnoh;Jin, Kyoung Bog
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.23 no.4
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    • pp.356-364
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    • 2013
  • This paper presents a tracking gain-up controller design method to control effectively the vibration of tracking actuator caused by external shocks and remaining velocity after seek control. A pole placement constraint is considered to assure a desired transient response against the vibration of tracking actuator. A loop gain-up constraint is introduced to hold the tracking gain-up loop gain and control bandwidth within allowable bounds. The pole placement constraint is expressed by a matrix inequality and the loop gain-up constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a tracking gain-up controller is obtained by integrating a genetic algorithm with LMI design approach. The proposed tracking gain-up controller design method is applied to the track-following system of a DVD recording device and its effectiveness is evaluated through the experimental results.

Design fuzzy-genetic controller for path tracking in wheeled-mobile robot (구륜 이동 로보트의 경로 추적을 위한 Fuzzy-Genetic Controller 설계)

  • 김상원;김성희;박종국
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.512-515
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    • 1997
  • In this paper the fuzzy-genetic controller for path-tracking of WMRs is proposed. Fuzzy controller is implemented to adaptive adjust the crossover rate and mutation rate, and genetic algorithm is implemented to adaptive adjust the control gain during the optimization. The computer simulation shows that the proposed fuzzy-genetic controller is effective.

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Design of an Intelligent Controller of Mobile Robot Using Genetic Algorithm (제네틱 알고리즘을 이용한 이동로봇의 지능제어기 설계)

  • 정동연;김종수;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.207-212
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    • 2003
  • This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

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Genetic algorithm-based ultra-efficient MPP tracking in a solar power generation system (태양광 발전 시스템의 효율증대를 위한 Genetic Algorithm을 적용한 MPPT Control)

  • Choi, Dae-Seub
    • Proceedings of the KIEE Conference
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    • 2006.07b
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    • pp.1187-1188
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    • 2006
  • This paper a new method which applies a genetic algorithm for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. In addition, the proposed method introduces a ultra efficient MPP tracking in a solar power generation system.

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A Robust Track-following Control with Multiple Constraints Using Genetic Algorithm (유전자 알고리즘을 이용한 다중 제한 조건을 만족하는 강인 트랙 추종 제어)

  • Lee, Moon-Noh;Lee, Hong-Kyu;Jin, Kyoung-Bog
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.22 no.3
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    • pp.275-283
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    • 2012
  • This paper presents a design method of a robust tracking controller satisfying multiple constraints using genetic algorithm. A robust $H_{\infty}$ constraint with loop shaping is used to address disturbance attenuation with error limits and a loop gain constraint is considered so as not to enlarge the tracking loop gain and bandwidth unnecessarily. The robust $H_{\infty}$ constraint is expressed by a matrix inequality and the loop gain constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a robust tracking controller can be obtained by integrating genetic algorithm with LMI approach. The proposed tracking controller design method is applied to the track-following system of an optical DVD recording drive and is evaluated through the experimental results.

Development of Genetic Algorithm for Robust Control of Mobile Robot (모바일 로봇의 견실제어를 위한 제네틱 알고리즘 개발)

  • 김홍래;배길호;정경규;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2004.04a
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    • pp.241-246
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    • 2004
  • This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

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The Real-time Neural Network Control of Mobile Robot Based-on Genetic Algorithm (유전 알고리즘을 이용한 이동로봇의 실시간 신경회로망 제어)

  • 정경규;김종수;이우송;이명재;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.561-566
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    • 2002
  • This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

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