This paper presents an adaptive iterative learning control scheme that is applicable to a class of nonlinear systems. The control scheme guarantees system stability and boundedness by using the feedback controller coupled with the fuzzy compensator and achieves precise tracking by using the iterativ
Control of rotational molding using adaptive fuzzy systems
β Scribed by D. I. Abu-Al-Nadi; D. I. Abu-Fara; I. Rawabdeh; R. J. Crawford
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 476 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0730-6679
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β¦ Synopsis
Abstract
Rotational molding is a method for manufacturing hollow plastic parts. In the work reported here, adaptive fuzzy logic techniques have been used to relate the machine oven temperature to other manipulated parameters of the process. The objective is to design a reliable control system for the rotational molding process. An adaptive fuzzy network was developed to correlate changes in oven temperature to changes in the opening of the control valve on the fuel system. The network parameters were optimized using realβvalued genetic algorithms. This network gave good results when its performance was compared with experimental data from a commercial rotational molding machine. The network was successfully utilized to design a control system, which works well in regard to set point tracking and load rejection. Β© 2005 Wiley Periodicals, Inc. Adv Polym Techn 24: 266β277, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.20047
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