Intelligent identification of uncertainty bounds for robust servo controlled system

M. Raafat, Safanah and Akmeliawati, Rini and Martono, Wahyudi (2010) Intelligent identification of uncertainty bounds for robust servo controlled system. In: 2010 International Conference on Computer Applications and Industrial Electronics (ICCAIE 2010), December 5-7, 2010, Kuala Lumpur, Malaysia, 5-7 Dec., 2010, Kuala Lumpur.

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Abstract

In this paper a new intelligent identification method of uncertainty bound utilizes an adaptive neurofuzzy inference system (ANFIS) in a feedback scheme isnproposed. The proposed ANFIS feedback structurenperforms better in determining the uncertainty bounds withnminimum number of iterations and error. In our proposedntechnique, the intelligent identified uncertainty weightingnfunction is validated utilizing v-gap to ensure the stability of the designed H� controlled system. Our proposed intelligent identification of uncertainty bound is demonstrated on a servo motion system. Simulation and experimental results show that the new ANFIS identifier is more reliable and highly efficient in estimating the best uncertainty weightingnfunction for robust controller design

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	5806/5385
Uncontrolled Keywords:	adaptive neuro-fuzzy inference system, ANFIS; H� robust controller; identification; servo positioning system; uncertainty bound; v-gap.
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Prof. Dr. Rini Akmeliawati
Date Deposited:	02 Nov 2011 14:01
Last Modified:	25 Jan 2012 08:19
URI:	http://irep.iium.edu.my/id/eprint/5385

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