Purpose:This paper presents a novel intelligent backstepping sliding mode control for an experimental permanent magnet synchronous motor. Design/methodology/approach: A novel recurrent RBFN is used to is used to approximate unknown nonlinear functions in 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. Since the type-2 fuzzy logic has higher flexibility and higher approximation ability than type-1 fuzzy, so in this paper type-2 fuzzy logic has been used. In order to ensure the efficiency and performance of the proposed control method, proof of its convergence has also been done. Findings: Experimental results indicate the appropriate performance of the proposed method.
