Paper
13 October 2008 A new model reference adaptive control method based on neural network for servo system
Hongjie Hu, Bo Zhao
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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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongjie Hu and Bo Zhao "A new model reference adaptive control method based on neural network for servo system", 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); https://doi.org/10.1117/12.807399
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Cited by 1 scholarly publication.
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KEYWORDS
Neural networks

Control systems

Servomechanisms

Adaptive control

Device simulation

Mathematical modeling

Systems modeling

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