PSO-Based PI parameter optimization for PMSM speed control with FOC method

Abstract

Permanent Magnet Synchronous Motors (PMSMs) are widely employed in automotive applications, industrial automation, and household appliances due to their high efficiency, compact structure, and ability to deliver high torque with low power consumption. Along with the rapid growth of the global permanent magnet motor market, control strategies play a crucial role in ensuring optimal motor performance. Among these strategies, Field-Oriented Control (FOC) has become an industrial standard owing to its fast dynamic response and high control accuracy. In FOC schemes, Proportional–Integral (PI) controllers are essential components in both current and speed control loops. However, conventional PI controllers suffer from limitations, particularly in the parameter tuning process for complex and nonlinear systems. Traditional tuning methods, such as Ziegler–Nichols and manual trial and error approaches, are time-consuming and may result in suboptimal system performance. To address these issues, this study proposes the application of the Particle Swarm Optimization (PSO) algorithm to automatically tune the PI controller parameters in the FOC speed control loop. MATLAB simulation results demonstrate that the PSO-optimized PI-based FOC significantly improves dynamic performance compared to conventional FOC, as evaluated by time-domain parameters including rise time, overshoot, and steady-state error. Under both no-load and load conditions, the PSO-based FOC exhibits faster response, reduced overshoot, and lower steady-state error. These findings indicate that PSO-based FOC has strong potential to enhance the stability and speed response quality of PMSM drives, making it a promising approach for further development and real-world implementation.