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Research Papers

Modeling of Dynamic Systems Using Orthogonal Endocrine Adaptive Neuro-Fuzzy Inference Systems

[+] Author and Article Information
Marko Milojković

Assistant Professor
Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: marko.milojkovic@elfak.ni.ac.rs

Dragan Antić

Professor
Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: dragan.antic@elfak.ni.ac.rs

Miroslav Milovanović

Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: miroslav.b.milovanovic@elfak.ni.ac.rs

Saša S. Nikolić

Assistant Professor
Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: sasa.s.nikolic@elfak.ni.ac.rs

Staniša Perić

Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: stanisa.peric@elfak.ni.ac.rs

Muhanad Almawlawe

Faculty of Electronic Engineering,
Department of Control Systems,
University of Niš,
Aleksandra Medvedeva 14,
Niš 18000, Republic of Serbia
e-mail: muhanadhashim@gmail.com

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 9, 2015; final manuscript received May 29, 2015; published online July 10, 2015. Assoc. Editor: Dumitru I. Caruntu.

J. Dyn. Sys., Meas., Control 137(9), 091013 (Jul 10, 2015) (6 pages) Paper No: DS-15-1098; doi: 10.1115/1.4030758 History: Received March 09, 2015

This paper presents a new method for designing adaptive neuro-fuzzy inference systems (ANFIS). Improvements are made by introducing specially developed orthogonal functions into the very structure of ANFIS, specifically, into the layer that imitates Sugeno stile defuzzification. These functions are specially tailored for analysis and synthesis of dynamic systems and they also contain an adaptive measure of the variability of the systems operating in a real environment, which can be implemented inside the ANFIS as hormonal effect.

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References

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Figures

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Fig. 1

The structure of OEANFIS with two inputs

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Fig. 3

Input and output training sets

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Fig. 2

The modular servo system setup

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Fig. 4

Training data and model responses

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Fig. 5

Checking data and model responses

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