MRAS-Based Speed Sensorless Control of Induction Motor Model

This text discusses the MRAS (Model Reference Adaptive System) method for controlling induction motor models without requiring speed sensors, resulting in simplified system architecture and reduced costs. The implementation typically involves designing a reference model representing the ideal motor dynamics and an adjustable model that adapts its parameters to minimize the error between the two models. Key functions include rotor flux estimation and speed calculation through adaptive mechanisms like Popov's hyperstability theory or gradient methods. The method supports closed-loop control configurations and can be directly deployed to dSpace real-time control platforms through automatic code generation from MATLAB/Simulink models. This integration enhances control precision and reliability by enabling real-time parameter tuning and performance monitoring. The MRAS approach also demonstrates adaptability to other motor control systems including synchronous motors and permanent magnet synchronous motors (PMSM), showing broad application prospects and research value through modifications in reference model design and adaptation laws. Therefore, the MRAS methodology holds significant importance in motor control domains, warranting in-depth research and practical applications through systematic implementation involving error calculation blocks, adaptive mechanism coding, and real-time interface configuration for control hardware.