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.
The significance of Permanent Magnet Synchronous Motors (PMSM) is that it offers high performance and efficiency for motor drives. The controlling of the high-performance motor is characterized by smooth operation of the motor over entire speed range, control ability of torque even at zero speed, fast acceleration, and deceleration. The optimization of the speedcontrol performance under different constraints and uncertainties is the biggest concern in PMSM. In that sense, various speedcontrol mechanisms were presented towards identifying the better way to control PMSM drive having high-speed features and desired torque response. However, it is necessary to have a suitable control mechanism where the better adjustment of performance can be achieved for a different operating condition. However, it is quite hard to distinguish the system characteristics and dynamic control parameters during real-time operation due to complexity in PMSM system. This paper intends to present the survey of controlling strategies in PMSM and current research trends in PMSM. Along with the research gap, a futuristic line of research is presented.
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