文章基本信息

标题：Self-Tuning Vibration Control of a Rotational Flexible Timoshenko Arm Using Neural Networks
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作者：Minoru Sasaki ; Toshimi Shimizu ; Yoshihiro Inoue 等
期刊名称：Advances in Acoustics and Vibration
印刷版ISSN：1687-6261
电子版ISSN：1687-627X
出版年度：2012
卷号：2012
DOI：10.1155/2012/852780
出版社：Hindawi Publishing Corporation
摘要：A self-tuning vibration control of a rotational flexible arm using neural networks is presented. To the self-tuning control system, the control scheme consists of gain tuning neural networks and a variable-gain feedback controller. The neural networks are trained so as to make the root moment zero. In the process, the neural networks learn the optimal gain of the feedback controller. The feedback controller is designed based on Lyapunov's direct method. The feedback control of the vibration of the flexible system is derived by considering the time rate of change of the total energy of the system. This approach has the advantage over the conventional methods in the respect that it allows one to deal directly with the system's partial differential equations without resorting to approximations. Numerical and experimental results for the vibration control of a rotational flexible arm are discussed. It verifies that the proposed control system is effective at controlling flexible dynamical systems.