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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ying-Chih Hung Faa-Jeng Lin |
| Copyright Year | 2009 |
| Abstract | A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM) in this study. First, the structure and operating principles of the LUSM are introduced. Since the dynamic characteristics and motor parameters of the LUSM are nonlinear and time-varying, an RWNN controller is designed to improve the control performance for the precision tracking of various reference trajectories. The network structure and its on-line learning algorithm using delta adaptation law of the RWNN are described in detail. Moreover, an FPGA chip is adopted to implement the developed control algorithm for possible low-cost and high-performance industrial applications. Finally, the effectiveness of the proposed control system is verified by some experimental results. |
| Starting Page | 1290 |
| Ending Page | 1295 |
| File Size | 399524 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424447350 |
| DOI | 10.1109/ISDA.2009.61 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-11-30 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Recurrent neural networks Uncertainty Industrial control Neural networks Control systems Electrical equipment industry Motion control Field programmable gate arrays Centralized control Construction industry |
| Content Type | Text |
| Resource Type | Article |
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