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Neural Network Approximation Based Multi-dimensional Active Control of Regenerative Chatter in Micro-milling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9719))

Abstract

In this paper, an active control approach with the employments of two piezoelectric actuators, the Neural Networks (NNs) as approximators and the Lyapunov-Krasovskii functional which is used to deal with the time delayed tool vibrations is investigated for suppressing the 2-dof regenerative chatter in micro-milling. A dynamic model of micro-milling process and corresponding controlled system are established. Simulations are presented to validate the control performances of developed control approach.

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Correspondence to Chun-Yi Su .

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Liu, X., Su, CY., Li, Z. (2016). Neural Network Approximation Based Multi-dimensional Active Control of Regenerative Chatter in Micro-milling. In: Cheng, L., Liu, Q., Ronzhin, A. (eds) Advances in Neural Networks – ISNN 2016. ISNN 2016. Lecture Notes in Computer Science(), vol 9719. Springer, Cham. https://doi.org/10.1007/978-3-319-40663-3_29

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  • DOI: https://doi.org/10.1007/978-3-319-40663-3_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40662-6

  • Online ISBN: 978-3-319-40663-3

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