Adaptive PIF control for permanent magnet synchronous motors based on GPC

Area of Science:

• Electrical Engineering
• Control Systems
• Robotics

Background:

• Permanent magnet synchronous motors (PMSMs) are crucial in various industrial applications.
• Traditional PI or PIF controllers often face limitations in dynamic performance and adaptability.
• Enhancing speed control precision and robustness in PMSMs is an ongoing challenge.

Purpose of the Study:

• To propose a novel generalized predictive control (GPC)-based proportional integral feedforward (PIF) controller for PMSM speed control.
• To improve the tracking performance of PMSM speed control systems under varying operating conditions.
• To extend the application of GPC principles to replace conventional controllers in industrial settings.

Main Methods:

• Online identification of motor model parameters to adapt control parameters.
• Implementation of a simplified GPC law to provide suitable control parameters for the PIF controller.
• Detailed discussion and adaptation of the speed reference curve for continuity and differentiability requirements.

Main Results:

• The proposed GPC-based PIF controller significantly enhances the speed control system's performance.
• Improved tracking of specified speed signals is achieved due to adaptive control parameters.
• Experimental results validate the efficacy and usefulness of the developed controller.

Conclusions:

• The GPC-based PIF controller offers a superior alternative to traditional PI or PIF controllers for PMSM speed control.
• The controller demonstrates robustness and adaptability to uncertainties in operating conditions.
• This research successfully extends GPC application for improved industrial motor control.