Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous...

Area of Science:

• Electrical Engineering
• Control Systems
• Fuzzy Logic

Background:

• Interior Permanent Magnet Synchronous Motors (IPMSMs) present complex nonlinear dynamics.
• Accurate position tracking is crucial for many IPMSM applications.
• Existing control methods often involve numerous parameters and struggle with system nonlinearities.

Purpose of the Study:

• To develop a discrete-time adaptive position tracking control strategy for IPMSMs.
• To utilize fuzzy logic systems for approximating nonlinearities in the IPMSM drive system.
• To design a controller with a reduced number of adjustable parameters.

Main Methods:

• Discretization of the IPMSM drive system using the Euler method.
• Application of fuzzy logic systems to approximate system nonlinearities.
• Design of a discrete-time fuzzy controller using the backstepping approach.

Main Results:

• The proposed controller effectively overcomes coupling nonlinearities in the IPMSM system.
• The number of adjustable parameters is significantly reduced to only two.
• Guaranteed convergence of tracking errors to a small neighborhood of the origin.
• All system signals are demonstrated to be bounded.

Conclusions:

• The discrete-time fuzzy controller offers an effective and simplified solution for IPMSM position tracking.
• The method successfully handles complex nonlinear dynamics with fewer parameters.
• Simulation results validate the theoretical findings and demonstrate practical potential.