Advances in Control for Permanent Magnet Synchronous Motor (PMSM)

Dear Colleagues,

A Permanent Magnet Synchronous Motor (PMSM) has been widely used in various applications, such as robotics, machine tools, actuators, servo systems, transportation electrification, wind power generation, etc. Control techniques play a key role in the PMSM drive systems. Current vector control (CVC) is suitable for surface-mounted PMSM (SPMSM) since flux-weakening is merely required and the electrical parameters of PMSM are nearly constant or slow-varying so that the torque and flux can be well-controlled using the current model. However, for interior PMSM (IPMSM), direct torque and flux control (DTFC) is more appropriate because the inductance is easily to vary with operating conditions. To improve the robustness to parameter variations, the voltage model or mixed model should be used for torque and flux observation. Moreover, the stator flux can be controlled directly using DTFC so that deep flux-weakening for IPMSM can be achieved easily. Nevertheless, there are a lot of restrictions on the actual control quantities, e.g., the maximum duty ratio is no more than 100%, torque or current should be limited for safety consideration, and switching loss is essential for high-power applications. Therefore, model predictive control becomes an emerging technique due to its ability to deal with multiple restrictions simultaneously. Nevertheless, the control performance of MPC relies on the accuracy of the mathematical model. To enhance the robustness, observers, such as disturbance observer and extended state observer, and model-free techniques, such as neural network and data-driven, can be employed. Nowadays, with the development of technology, requirements of stronger stability, higher reliability, higher efficiency, higher power density or torque density, higher dynamics, and lower cost become a challenge for existing control schemes. More efforts should be made to develop advanced control techniques for various kinds of applications.

This Special Issue is dedicated to collecting and sharing the latest research and the newest ideas from both industry and academia about the advanced control strategies for PMSM in different applications. Topic of interest include, but are not limited to:

• Torque and flux control;
• Speed and position control;
• Sensorless control;
• Information reconstruction;
• Fault diagnosis and fault-tolerant control;
• Model-free adaptive control;
• Artificial intelligence and data-driven.

Dr. Yuefei Zuo
Dr. Xiaogang Lin
Guest Editors

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• active disturbance rejection control
• adaptive control
• artificial intelligence
• current reconstruction
• deadbeat control
• direct torque and flux control
• fault diagnosis
• fault-tolerant control
• flux weakening
• harmonic utilization and suppression
• maximum torque per ampere
• model predictive control
• neural network
• overmodulation
• parameter identification
• sensorless control
• sliding mode control