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Erschienen in: International Journal of Machine Learning and Cybernetics 3/2019

09.10.2017 | Original Article

Adaptive control of nonlinear fractional-order systems using T–S fuzzy method

verfasst von: Saeed Mirzajani, Mohammad Pourmahmood Aghababa, Aghileh Heydari

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 3/2019

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Abstract

Owing to the superior capability of fractional differential equations in modeling and characterizing accurate dynamical properties of many high technology real world systems, the design and control of fractional-order systems have captured lots of attention in recent decades. In this paper, an adaptive intelligent fuzzy approach to controlling and stabilization of nonlinear non-autonomous fractional-order systems is proposed. Since dynamic equations of applied fractional-order systems usually contain various parameters and nonlinear terms, the Takagi–Sugeno (T–S) fuzzy models with if-then rules are adopted to describe the system dynamics. Also, as the nonlinear system parameters are assumed to be unknown, adaptive laws are derived to estimate such fluctuations. Simple adaptive linear-like control rules are developed based on the T–S fuzzy control theory. The stability of the resulting closed loop system is guaranteed by Lyapunov’s stability theory. Two illustrative numerical examples are presented to emphasize the correct performance and applicability of the proposed adaptive fuzzy control methodology. It is worth to notice that the proposed controller works well for stabilization of a wide class of either autonomous nonlinear uncertain fractional-order systems or non-autonomous complex systems with unknown parameters.

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Metadaten
Titel
Adaptive control of nonlinear fractional-order systems using T–S fuzzy method
verfasst von
Saeed Mirzajani
Mohammad Pourmahmood Aghababa
Aghileh Heydari
Publikationsdatum
09.10.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 3/2019
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0733-1

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