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Melt temperature learning control of injection molding process based on CMAC neural network
-
Yonggang Peng
and
Wei Wei
Published/Copyright:
April 20, 2011
Abstract
Accurately monitoring and controlling melt temperature in the injection molding process can be a challenge. A barrel temperature model was achieved with the use of a system modeling method. Because of time variance, uncertainty and non-linearity of injection molding barrel temperature, a learning control method based on the use of a cerebellar model articulation controller (CMAC) neural network was proposed. Simulations and experimental results have demonstrated that this method elicits high response speed and excellent control accuracy of barrel melt temperature.
Keywords: cerebellar model articulation controller (CMAC); coupling; injection molding machine; learning control; melt temperature
Published Online: 2011-04-20
Published in Print: 2011-04-01
©2011 by Walter de Gruyter Berlin New York
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Keywords for this article
cerebellar model articulation controller (CMAC);
coupling;
injection molding machine;
learning control;
melt temperature
Articles in the same Issue
- Publisher’s Note
- A new start for Journal of Polymer Engineering
- News
- Implementing a new manuscript submission system
- Original Articles
- Model for the hydrodynamic dispersion of agglomerates incorporating thermoresponsive additives
- Preparation and properties of PLA/long alkyl chain modified multi-walled carbon nanotubes nanocomposites
- Insights into the slip flow phenomena encountered during in-mold coating (IMC) of plastic parts
- Physical properties of biaxially oriented PA6 film for simultaneous stretching and sequential processing
- Synthesis and solution behaviors of star hydrophobically modified acrylamide copolymers
- Melt temperature learning control of injection molding process based on CMAC neural network
- Numerical analysis of mixing performance of mixing section in pin-barrel single-screw extruder
- New process technology for high volume production of composites
