ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
A variable interval fuzzy quantification algorithm with self-adjustable factor in fulldomain is proposed in this paper. It focuses on digital inverted plasma arc cutting power and studiesstrong nonlinearity and uncertainty of power. The neural network is also introduced to decouplecutting parameters variables in the multi-parameters coupling cutting process. This algorithm avoidscomplex nonlinear system modeling and realizes real-time and effective online control of cuttingprocess by combining advantages of fuzzy control and neural network control. Furthermore, theoptimized fuzzy control improves steady-state precision and dynamic performance of systemsimultaneously. The experimental result shows that this control improves precision, ripples, finishand other comprehensive index of work piece cut, and plasma arc cutting power supply based onfuzzy-neural network has excellent control performance
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/57/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.392-394.735.pdf
