Adaptive model-free coupling controller design for multi-axis motion systems

Bo Sheng Chen, Ching Hung Lee*

*此作品的通信作者

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

摘要

In this study, we introduce an adaptive model-free coupling controller while using recurrent fuzzy neural network (RFNN) for multi-axis system to minimize the contour error. The proposed method can be applied to linear or nonlinear multi-axis motion control systems following desired paths. By the concept of cross-coupling control (CCC), multi-axis system is transferred into a nonlinear time-varying system due to the time-dependent coordinate transformation; tangential, normal, and bi-normal components of desired contour. Herein, we propose a model-free adaptive coupling controller design approach for multi-axis linear motor system with uncertainty and nonlinear phenomena. RFNN establishes the corresponding adaptive coupling controller to treat the uncertain system with nonlinear phenomenon. The stability of closed-loop system is guaranteed by the Lyapunov method and the adaptation of RFNN is also obtained. Simulation results are introduced in order to illustrate the effectiveness.

原文English
文章編號3592
期刊Applied Sciences (Switzerland)
10
發行號10
DOIs
出版狀態Published - 1 5月 2020

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