Abstract
Advanced internal combustion engine piston is designed with middle-convex contour and variable ellipticity section for better working performance. Machining system shows significantly multi-input multi-output and nonlinear behaviors when turning this piston profile on NC lathe. These behaviors lead to an obvious error between machined parts to the desired profile. Traditional error compensation method for linear system cannot assure the required accuracy. Therefore, an artificial neural network (NN) inverse control method is proposed for high profile accuracy. A multilayered feedforward neural network is designed for this multi-input multi-output system and trained off-line to identify the inverse model of the machining system. Then the inverse model is employed to tune the system online. It is shown, by experiments of piston turning, that this control scheme can improve the machining accuracy effectively.
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© 2007 Springer-Verlag Berlin Heidelberg
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Liu, T., Yang, X., Wang, J. (2007). Neural Network Inverse Control for Turning Complex Profile of Piston. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_66
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DOI: https://doi.org/10.1007/978-3-540-74769-7_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74768-0
Online ISBN: 978-3-540-74769-7
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