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Proceedings Paper

RBFNN speed compensate controller use in high precision servo systems
Author(s): Hongjie Hu; Dedi Li
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Paper Abstract

This paper proposed three control schemes using model reference adaptive control (MRAC) and RBF neural network(RBFNN). Through comparision, it proposed a MRAC scheme with RBFNN compensator for speed control of high precision servo systems. The MRAC scheme is used to give better solutions with online adaptation and guarantee the stablity of the system. In the feedback channel, the parameter Kp makes it easier to design the system poles. By using a PI controller before Kp, the dynamic performance of the system is improved. As a speed compensate controller, the RBFNN is designed parallel with the model reference control. The RBFNN controller is able to online learn the unknown model dynamics, parameter variation and disturbance of the system. Thus, it is feasible to preserve favorable model-following characteristics under various conditions. The effectiveness of the proposed control scheme is demonstrated by simulation. It is found that the proposed scheme can reduce the plant's sensitivity to parameter variation and disturbance. High precision performance is obtained when given constant and sine wave disturbance at the same time.

Paper Details

Date Published: 13 October 2008
PDF: 6 pages
Proc. SPIE 7129, Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration, 71291A (13 October 2008); doi: 10.1117/12.807394
Show Author Affiliations
Hongjie Hu, BeiHang Univ. (China)
Dedi Li, BeiHang Univ. (China)


Published in SPIE Proceedings Vol. 7129:
Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration

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