Intelligent monitoring of PMSM based on adaptive fuzzy logic for diagnosis

In this paper, the fuzzy adaptive gain monitoring method (AGFLC) uses direct field-oriented control (DFOC) to monitor the speed of permanent magnet synchronous motors (PMSM). This surveillance strategy can detect the error of the velocity parameter, forcing the monitored system to achieve the desired reference model, and eliminating the velocity error. First, we examine the mathematical model describing the internal behavior of PMSM to design our system based on the priory physical model of the system. Then, we propose an intelligent method that combines a fuzzy control algorithm with its related control rules, aiming to monitor the speed of PMSM. This problem is solved by combining the two parameters of error and its variation. A fuzzy algorithm has proven to be an effective method to adjust the speed by suppressing disturbances. Furthermore, an adapted gain fuzzy controller, which provides a fast dynamic response without overshooting at various dynamic actions, has been suggested to compensate for all external disturbances. The obtained simulation results demonstrate the efficiency of the monitoring method for fault detection and localization and verify the performance of the adaptive algorithm control system.