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Position Control of Linear Synchronous Motor by Dual Learning

Jung Il Park, Sung Ho Suh, Umirov Ulugbek
JKSPE 2012;29(1):79-86.
Published online: January 1, 2012
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This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.

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Position Control of Linear Synchronous Motor by Dual Learning
J. Korean Soc. Precis. Eng.. 2012;29(1):79-86.   Published online January 1, 2012
Download Citation

Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

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Position Control of Linear Synchronous Motor by Dual Learning
J. Korean Soc. Precis. Eng.. 2012;29(1):79-86.   Published online January 1, 2012
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