Intelligent complementary sliding-mode control for lusms-based X-Y-Ø motion control stage

Faa Jeng Lin, Syuan Yi Chen, Kuo Kai Shyu, Yen Hung Liu

研究成果: 雜誌貢獻文章同行評審

13 引文 斯高帕斯(Scopus)

摘要

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-Ø motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.

原文英語
文章編號5507665
頁(從 - 到)1626-1640
頁數15
期刊IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
57
發行號7
DOIs
出版狀態已發佈 - 2010 七月 1

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

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