Fuzzy Control Based on Genetic Algorithm to Optimize the Mill Load

Yan Jiao Li; Jian Min Wang; Jie Zhang

doi:10.4028/www.scientific.net/AMM.385-386.827

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 385-386Fuzzy Control Based on Genetic Algorithm to...

Fuzzy Control Based on Genetic Algorithm to Optimize the Mill Load

Abstract:

Mill load is closely related to production efficiency and energy consumption, the purpose of mill load control is guaranteed to increase the production efficiency under the condition of safe and stable operation of the mill grinding. For ball grinding system has some characteristics of nonlinear, large time delay and time-varying, the conventional control method is hard to achieve good control effect, this paper proposes a optimization method of fuzzy control of mill load based on genetic algorithm. The control rules and membership functions has a great deal of subjectivity and arbitrariness. In order to make up this deficiency, using genetic algorithm better solve the mill load optimization. Make grinding system can safe, stable and efficient operation.

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Periodical:

Applied Mechanics and Materials (Volumes 385-386)

Pages:

827-830

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.385-386.827

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Online since:

August 2013

Authors:

Yan Jiao Li, Jian Min Wang, Jie Zhang

Keywords:

Fuzzy Control, Genetic Algorithm (GA), Mill Load, Optimization

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