Title: Sliding mode with neuro-fuzzy network controller for inverted pendulum

Authors: Fatima Zohra Daikh; Mohamed Fayçal Khelfi

Addresses: Faculty of Exact and Applied Sciences, Department of Computer Sciences, University of Oran, Oran, Algeria ' Faculty of Exact and Applied Sciences, Department of Computer Sciences, Laboratory of Research in Industrial Computing and Networks, University of Oran, Oran, Algeria

Abstract: This paper presents a sliding mode with fuzzy-neural network controller for nonlinear systems. The proposed controller combines the advantages of second order sliding mode control and fuzzy neural. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. The sliding mode control (SMC) system which is insensitive to uncertainties, including parameter variations and external disturbances in the whole control process. The fuzzy-neural network mainly self-tuning fuzzy inference system (STFIS) is used to approximate the unknown system functions and switch item. Finally, the sliding-mode with fuzzy-neural network control is used to control single inverted pendulum and confirms the validity of the proposed approach. Results of simulations containing tests of robustness are presented.

Keywords: sliding mode control; SMC; neuro-fuzzy control; inverted pendulum; self-tuning FIS; STFIS; controller design; network control; artificial neural networks; ANNs; fuzzy inference systems; fuzzy logic; nonlinear systems; simulation; stability; robust control; uncertainties.

DOI: 10.1504/IJAAC.2015.068043

International Journal of Automation and Control, 2015 Vol.9 No.1, pp.24 - 36

Received: 29 May 2014
Accepted: 15 Jul 2014

Published online: 15 Mar 2015 *

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