Abstract
A two-stage structure model was developed for the vibration control of an actuator platform and a controller based on a three-layer neural network was applied to realize high performance control for the kickstand disturbance of a block forming machine. This paper presents a survey of the basic theory of the back-propagation(BP) neural network architecture including its architectural design, BP algorithm, the root mean square error (RMSE) and optimal model establishment. The situ-test data of the control system were measured by acceleration transducer and the experimental results indicates that the proposed method was effective. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Wu, Q., Zhang, Q., Zong, C., & Cheng, G. (2007). Vibration control of block forming machine based on an artificial neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 231–240). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_28
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