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J. Tavoosi (2020)
Stable Backstepping Sliding Mode Control Based on ANFIS2 for a Class of Nonlinear Systems
The purpose of this paper is to present a novel intelligent backstepping sliding mode control for an experimental permanent magnet synchronous motor.Design/methodology/approachA novel recurrent radial basis function network (RBFN) is used to is used to approximate unknown nonlinear functions in permanent magnet synchronous motor (PMSM) dynamics. Then, using the functions obtained from the neural network, it is possible to design a model-based and precise controller for PMSM using the immersive modeling method.FindingsExperimental results indicate the appropriate performance of the proposed method.Originality/valueThis paper presents a novel intelligent backstepping sliding mode control for an experimental permanent magnet synchronous motor. A novel recurrent RBFN is used to is used to approximate unknown nonlinear functions in PMSM dynamics.
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing
Published: Dec 15, 2020
Keywords: Control systems; Fuzzy control; Power electronic devices modeling; Sliding mode control; Recurrent RBFN; Stability analysis; PMSM.
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