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Article type: Research Article
Authors: Vahedi, Mojtaba* | Hadad Zarif, Mohammad | Akbarzadeh Kalat, Ali
Affiliations: Department of Electrical and Robotic Engineering, University of Shahrood, Shahrood, Iran
Correspondence: [*] Correspondence to: Mojtaba Vahedi, Department of Electrical and Robotic Engineering, University of Shahrood, Shahrood, P.o. box 36199-95161, Iran. Tel.: +98 9124734622; [email protected]
Abstract: This paper presents a novel approach for robust speed control of medium size induction motors using neuro-fuzzy dynamic sliding mode control. First, a simple dynamic model of induction motors is introduced. Then, a conventional sliding mode control is presented. To reduce the chattering phenomenon, dynamic sliding mode control is designed using a secondary PID-type sliding surface. Moreover, in order to eliminate the tedious trial and error procedure in choosing a proper uncertainty upper bound, uncertainties have been estimated using a neuro-fuzzy system. The online training of the neuro-fuzzy dynamic sliding mode control is based on the adaptation law derived from the stability analysis. In addition, the reconstruction error of the neuro-fuzzy system is compensated to guarantee the asymptotic convergence of the speed tracking error. Simulation results verify that the neuro-fuzzy dynamic sliding mode control is robust against various uncertainties including parametric variations, external load disturbance, unmodeled dynamics and input voltage disturbances.
Keywords: Induction motor, neuro-fuzzy systems, dynamic sliding mode control, reconstruction error, Barbalat’s lemma
DOI: 10.3233/IFS-151601
Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 1, pp. 365-376, 2015
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