Model Reference Adaptive System-Based Sensorless Control of Permanent Magnet Synchronous Motors

This Simulink simulation demonstrates sensorless control of Permanent Magnet Synchronous Motors (PMSM) using the Model Reference Adaptive System (MRAS) approach. The implementation employs an adaptive observer that compares the outputs of a reference model (representing ideal motor behavior) with an adjustable model (estimating motor states). Key algorithmic components include rotor speed and position estimation through adaptive law integration, typically implemented using gradient or Lyapunov stability-based adaptation mechanisms. The simulation architecture features several critical function blocks: the MRAS estimator block handles parameter adaptation using error minimization between actual and estimated currents, while the speed controller utilizes PI regulators with anti-windup protection. The system achieves accurate speed and position control without physical sensors by continuously adjusting model parameters through real-time error correction algorithms. This control method finds significant applications in industrial automation, electric vehicles, and precision motion control systems. Through this simulation experiment, engineers can observe dynamic performance metrics, validate stability under varying load conditions, and optimize adaptation gains. The simulation enables comprehensive analysis of torque ripple characteristics, parameter sensitivity, and transient response behavior, providing valuable insights for practical implementation of MRAS-based sensorless control strategies in real-world PMSM drive systems.