A recent study led by Zhe Song from the Department of Electrical Engineering at Tsinghua University, Beijing, has introduced an innovative speed control method for permanent magnet synchronous motors (PMSM). This method, detailed in an article published in ‘IEEE Access’, aims to enhance the performance and reliability of PMSMs, which are widely used in various industrial applications, including robotics, electric vehicles, and renewable energy systems.
The research tackles a common challenge in motor control: the ability to maintain stable operation despite fluctuations in load and inertia. Traditional control methods often struggle with disturbances, leading to inefficiencies and potential failures in performance. To address this, Song and his team developed a disturbance-resistant adaptive fast super-twisting algorithm (FSTA) that significantly improves speed regulation.
One of the key innovations in this method is the introduction of a new reaching law that mitigates chattering—a problem often seen in sliding mode control systems. By incorporating an integral sliding surface, the researchers have reduced the need for precise acceleration inputs, which traditionally complicated control strategies. This results in a more stable system with decreased static errors.
Moreover, the team replaced the conventional sign function used in control algorithms with a continuous sigmoid function. This change enhances the system’s responsiveness and stability under varying operational conditions. As Song stated, “The proposed adaptive FSTA control method exhibits superior dynamic performance and stronger disturbance rejection capability against load and inertia.”
The commercial implications of this research are significant. Industries relying on PMSMs can expect improved efficiency and reliability in their operations, leading to cost savings and enhanced productivity. This technology could be particularly beneficial for sectors such as manufacturing, where precise motor control is essential for automation processes, and for electric vehicle manufacturers, where performance and battery efficiency are critical.
Furthermore, the integration of an extended sliding mode observer (ESMO) and a model reference adaptive system (MRAS) allows for real-time monitoring of load torque and rotational inertia. This adaptability not only boosts performance but also opens up opportunities for smarter motor control systems capable of adjusting to real-time conditions, thereby enhancing the overall operational efficiency.
As the demand for efficient and resilient motor control systems continues to grow, the advancements presented by Zhe Song and his team could pave the way for new applications and innovations in the energy sector. For more information on this research, you can visit Tsinghua University, where this groundbreaking work is taking place.
