El-bakkouri, Jamal (ENSEM of Casablanca, Hassan II University of Casablanca), MANSOURI, ADIL (SSDIA Laboratory, ENSET Mohammedia, Hassan II University of Casa), Ouadi, Hamid (Ismra), El Aoumari, Abdelaziz (ENSAM, Rabat), Giri, Fouad (University of Caen Normandie), Khafallah, Mohamed (University)

Position and Speed Estimation for a Surface-Mount PMSM Using RBFNN Observer with Stability Guarantee

Scheduled for presentation during the Invited Session "Advanced Control Techniques for Energy Conversion Systems-3" (ThuS3T3), Thursday, July 11, 2024, 15:50−16:10, Session room 3

12th IFAC Symposium on Control of Power & Energy Systems, July 10-12, 2024, Rabat, Morocco

This information is tentative and subject to change. Compiled on January 2, 2025

Abstract

This paper proposes a radial basis function neural network (RBFNN) observer for surface-mount permanent magnet synchronous motor (SPMSM). The corresponding observer is used to estimate the rotor speed, and the rotor position. The convergence of the observer estimation error is analyzed using Lyapunov theory, and uniformly ultimate boundedness stability is guaranteed. Simulation results are shown to confirm the effectiveness of the proposed observer.