Abstract:

Permanent Magnet Synchronous Motors (PMSM) have become a cornerstone in various industrial and technological applications due to their high efficiency, compact design, and superior dynamic performance. However, their nonlinear dynamics, parameter uncertainties, and sensitivity to external disturbances pose significant challenges to effective control. To address these limitations, Sliding Mode Control (SMC) has emerged as a robust solution, offering inherent disturbance rejection, resilience to parameter variations, and precise trajectory tracking.

This study explores traditional SMC approaches, including first-order methods and advanced variants such as integral and super-twisting sliding mode controllers. Key developments in these techniques—aimed at mitigating chattering, enhancing robustness, and improving convergence—are critically analyzed. A comparative evaluation of the methods is presented, emphasizing their respective advantages and limitations. The control algorithms are implemented in MATLAB/Simulink, with simulation results validating their performance under diverse operating conditions, including variable loads, parameter mismatches, and external disturbances.

The findings demonstrate that higher-order SMC techniques, particularly the super-twisting algorithm, significantly reduce chattering while maintaining robust tracking performance compared to conventional methods. These results underscore the potential of advanced SMC frameworks in real-world PMSM-driven systems, such as electric vehicles and industrial automation, where precision, reliability, and adaptability are critical.

Speaker Bio:

Mr. Abdullah Ajasa is currently pursuing a Master of Science in Systems & Control Engineering at King Fahd University of Petroleum & Minerals (KFUPM). He earned his Bachelor of Engineering in Mechanical Engineering from Olabisi Onabanjo University, Nigeria. His research interests include autonomous robotic manipulation, control of permanent magnet synchronous motors (PMSMs), quadcopter controller design, and mobile robotics navigation and control.