• Title/Summary/Keyword: Hyseresis

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Positioning control of pzt actuators using neuro control with hysteresis model (ICCAS 2003)

  • Lee, Byung-Ryong;Lee, Soo-Hee;Yang, Soon-Yong;Ahn, Kyung-Kwan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.382-385
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    • 2003
  • In this paper, in order to improve the control performance of piezoelectric actuator, an integrated control structure is proposed. The control structure consists of inverse hysteresis model , to compensate the hysteresis nonlinearty problem, and feedforward - feedback controller to give a good tracking performance. The inverse hysteresis model and neural network are used as feed-forward controller, and PID controller is used as a feedback controller. From diverse experiments it is concluded that the proposed control scheme gives good tracking performance than the classical control does.

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Precision Position Control System of Piezoelectric Actuator Using Inverse Hysteresis Modeling and Error Learning Method (역 히스테리시스 모델링과 오차학습을 이용한 압전구동기의 초정밀 위치제어)

  • 김형석;이수희;정해철;이병룡;안경관
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.383-388
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    • 2004
  • A piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearty is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearty can not be neglected. The hysteresis nonlinearty of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearty problem. And feedforward - feedback controller is proposed to give a good tracking performance. The Feedforward controller is inverse hysteresis model, Nueral network and PID control is used as a feedback controller. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded that the proposed control scheme gives good tracking performance

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Precision Position Control of Piezoactuator Using Inverse Hysteresis Model (역 히스테리시스 모델을 이용한 압전 구동기의 정밀위치 제어)

  • 김정용;이병룡;양순용;안경관
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.10a
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    • pp.349-352
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    • 1997
  • A Piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearity is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearity can not be neglected. The hysteresis nonlinearity of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearity problem. And feedforward-feedforward-feedback controller is proposed to give a good tracking performance. The Feedforward controller is inverse hysteresis model, and PID control is sued as a feedback controller. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded hat the proposed control scheme gives good tracking performance.

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Precision Position Control of Piezoelectric Actuator Using Feedforward Hysteresis Compensation and Neural Network (히스테리시스 앞먹임과 신경회로망을 이용한 압전 구동기의 정밀 위치제어)

  • Kim HyoungSeog;Lee Soo Hee;Ahn KyungKwan;Lee ByungRyong
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.7 s.172
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    • pp.94-101
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    • 2005
  • This work proposes a new method for describing the hysteresis non-linearity of a piezoelectric actuator. The hysteresis behaviour of piezoelectric actuators, including the minor loop trajectory, are modeled by geometrical relationship between a reference major loop and its minor loops. This hysteresis model is transformed into inverse hysteresis model in order to output compensated voltage with regard to the given input displacement. A feedforward neural network, which is trained by a feedback PID control module, is incorporated to the inverse hysteresis model to compensate unknown dynamics of the piezoelectric system. To show the feasibility of the proposed feedforward-feedback controller, some experiments have been carried out and the tracking performance was compared to that of simple PTD controller.