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An Adaptive Neuro-Fuzzy Architecture for Intelligent Control of a Servo System and its Experimental Evaluation. (Aras, Ayse Cisel.)
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An Adaptive Neuro-Fuzzy Architecture for Intelligent Control of a Servo System and its Experimental Evaluation.
Author:
 Aras, Ayse Cisel. Search Author in Amazon Books

Publisher:
IEEE,
ISBN:
 978-1-4244-6391-6
Edition:
 2010.
Classification:
 TK5105.5
URL:
http://library.neu.edu.tr:2048/login?url=http://dx.doi.org/10.1109/ISIE.2010.5637706
Detailed notes
    - In this paper the development of an adaptive neuro-fuzzy architecture for the speed control of a servo system with nonlinear load is presented. The synthesis of the structure is described and a learning algorithm for the neuro-fuzzy control system is derived. The supervised learning algorithm is used to train the unknown coefficients of the system, and then the fuzzy rules of the neuro-fuzzy system are generated. A number of simulation studies are carried out, and the results are compared with those obtained with a PI controller tuned using desired time response characteristics. These and the experimental studies presented show that the neuro-fuzzy control system has a better control performance than the conventional PI controller.
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EOL-17
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NEU Grand LibraryOnline (TK5105.5 .A5 2010)
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