DocumentCode :
1062299
Title :
Internal Model Control Based on a Neurofuzzy System for Network Applications. A Case Study on the High-Performance Drilling Process
Author :
Martín, Agustín Gajate ; Guerra, Rodolfo E Haber
Author_Institution :
Inst. de Autom. Ind., Spanish Council for Sci. Res., Madrid
Volume :
6
Issue :
2
fYear :
2009
fDate :
4/1/2009 12:00:00 AM
Firstpage :
367
Lastpage :
372
Abstract :
This paper presents the design and implementation of a neurofuzzy system for modeling and control of a high-performance drilling process in a networked application. The neurofuzzy system considered in this work is an adaptive-network-based fuzzy inference system (ANFIS), where fuzzy rules are obtained from input/output data. The design of the control system is based on the internal model control paradigm. The results obtained are significant both in simulation as well as the real-time application of networked control of the cutting force during high-performance drilling processes.
Keywords :
cutting; drilling; fuzzy control; fuzzy neural nets; fuzzy systems; adaptive-network-based fuzzy inference system; cutting force; high-performance drilling process; internal model control; networked control; High-performance drilling; internal model control; networked control; neurofuzzy systems;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2008.2006686
Filename :
4745833
Link To Document :
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