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Proceedings Paper

A new model reference adaptive control method based on neural network for servo system
Author(s): Hongjie Hu; Bo Zhao
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Paper Abstract

In this paper, a new model reference adaptive control (MRAC) scheme based on neural network (NN) for servo system position tracking control is proposed. This scheme consists of an MRAC controller and an online NN controller in velocity-loop. The velocity-loop is encircled with a position-loop which used a traditional PID controller. For reducing influence which arose from modeling error, unknown model dynamics, parameter variation and load changes on the velocity-loop, the NN controller is introduced to counteract the various influence mentioned above dynamically, adjust system to track the approximate velocity-loop reference model. The negative gradient method is used in MRAC and NN controller parameters update. In this way, the position-loop is not sensitive to the disturbance on velocity-loop, and the whole velocity-loop can be treated as a simple linear model when designing the other parts of the system. The simulation results show that the proposed method can counteract the disturbance effectively.

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, 71291C (13 October 2008); doi: 10.1117/12.807399
Show Author Affiliations
Hongjie Hu, Beihang Univ. (China)
Bo Zhao, 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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