An efficient Feed-forward compensation mechanism for NFC-based PMSM system using different observers for Load-torque estimation

Abstract

Permanent magnet synchronous motor (PMSM) offers high torque and efficiency and is used in most industrial applications. This manuscript uses a feed-forward compensation mechanism to design an efficient neuro-fuzzy logic controller (NFC) based surface-mounted PMSM system. The different load-observers like Discrete Luenberger Observer (DLO), Kalman filter observer (KFO), and discrete Kalman filter observer (DKFO) are used as a feed-forward compensation method to compensate the dq stator current and also estimate performance metrics. The NFC is used as a speed controller, and two PI controllers are used for the current control mechanism. The noise is added at the actual load torque and speed of PMSM and compensated using load observers. In this work, two different design scenarios are considered to analyze the performance metrics like load torque, speed, and position. The work also explores the average error that occurred at load torque, speed, and position during estimation. The NFC-based PMSM system improves the performance and utilizes less error over the PI/FLC-based PMSM using different observers.