A Neuroadaptive Position-Sensorless Robust Control for Permanent Magnet Synchronous Motor Drive System with Uncertain Disturbance
Omar Aguilar-Mejia,
Antonio Valderrabano-Gonzalez,
Norberto Hernández-Romero,
Juan Carlos Seck-Tuoh-Mora,
Julio Cesar Hernandez-Ochoa,
Hertwin Minor-Popocatl
Affiliations
Omar Aguilar-Mejia
Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico
Antonio Valderrabano-Gonzalez
Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico
Norberto Hernández-Romero
Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico
Juan Carlos Seck-Tuoh-Mora
Instituto de Ciencias Básicas e Ingeniería, Universidad Autónoma del Estado de Hidalgo, Área Académica de Ingeniería y Arquitectura, Pachuca 42184, Hidalgo, Mexico
Julio Cesar Hernandez-Ochoa
Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico
Hertwin Minor-Popocatl
School of Engineering, UPAEP University, 21 Sur 1103, Puebla 72410, Puebla, Mexico
The Permanent Magnet Synchronous Motor (PMSM) drive system is extensively utilized in high-precision positioning applications that demand superior dynamic performance across various operating conditions. Given the non-linear characteristics of the PMSM, a neuroadaptive sensorless controller based on B-spline neural networks is proposed to determine the control signals necessary for achieving the desired performance. The proposed control technique considers the system’s non-linearities and can be adapted to varying operating conditions, all while maintaining a low computational cost suitable for real-time operation. The introduced neuroadaptive controller is evaluated under conditions of uncertainty, and its performance is compared to that of a conventional PI controller optimized using the Whale Optimization Algorithm (WOA). The results demonstrate the viability of the proposed approach.
