【目的】永磁同步电机(PMSM)被广泛应用于伺服系统、电动汽车等领域，这些领域对电机控制的精度、响应速度和抗干扰能力要求较高。PMSM速度控制多采用比例积分微分(PID)控制，然而，传统PID控制器的线性结构在面对复杂的非线性系统时，难以提供PMSM所需的精确跟踪性能和抗干扰能力。针对此问题，本文提出了一种基于改进黑翅鸢算法(IBKA)的自抗扰控制(ADRC)策略。【方法】首先，在d-q坐标系下对PMSM进行建模和分析，并对PMSM速度控制器进行设计，采用非线性ADRC对PMSM的速度环进行控制，以增强系统对模型不确定性和外部扰动的鲁棒性。ADRC的核心优势在于其能够通过扩张状态观测器实时估计并补偿系统的总扰动，包括未建模动态和外部干扰，从而实现对系统状态的精确控制。然后，针对传统ADRC依赖经验进行参数整定的问题，提出了一种融合Tent混沌映射和高斯变异机制的IBKA，通过该算法实现ADRC参数的实时在线整定。最后，基于Matlab/Simulink进行仿真，验证本文所提基于IBKA优化的ADRC策略的有效性。【结果】仿真结果表明，相较于传统的比例积分(PI)控制和标准ADRC，基于IBKA优化的ADRC能够使PMSM表现出良好的动、静态性能，具有更快的响应速度、更好的跟踪精度、更强的抗干扰能力和更优的转矩控制能力。仿真结果不仅验证了IBKA在ADRC参数优化方面的有效性，还展示了ADRC在提高PMSM控制性能方面的潜力。【结论】本文提出的控制策略为PMSM在高精度、高动态和高抗干扰中的应用提供了一种有效的解决方案，具有一定的理论意义和应用价值。

[Objective] Permanent magnet synchronous motor (PMSM) is widely used in servo systems, electric vehicles and other fields, where high requirements exist for motor control accuracy, response speed, and anti-interference ability. The speed control of PMSM mostly adopts proportional integral differential (PID) control. However, the linear structure of traditional PID controllers struggles to provide the precise tracking performance and anti-interference ability required by PMSM when dealing with complex nonlinear systems. In order to address this issue, this paper proposes an active disturbance rejection control (ADRC) strategy based on the improved Black-winged Kite algorithm (IBKA). [Methods] Firstly, the PMSM was modeled and analyzed in the d-q coordinate system, and a speed controller for the PMSM was designed. Nonlinear ADRC was used to control the PMSM’s speed loop to enhance the system’s robustness against model uncertainties and external disturbances. The core advantage of ADRC is its ability to estimate and compensate for the total disturbance of the system in real time through the extended state observer, including unmodeled dynamics and external disturbances, thereby achieving precise control of the system state. Secondly, to address the issue of traditional ADRC relying on experience for parameter tuning, an IBKA algorithm that integrated Tent chaotic mapping and Gaussian mutation mechanism was proposed. This algorithm was used to achieve real-time online tuning of ADRC parameters. Finally, simulations based on Matlab/Simulink were conducted to verify the effectiveness of the ADRC strategy based on IBKA optimization proposed in this paper. [Results] The simulation results showed that compared with the traditional proportional integral (PI) control and standard ADRC, the ADRC based on IBKA optimization enabled the PMSM to exhibit good dynamic and static performance, with faster response speed, better tracking accuracy, stronger anti-interference ability, and superior torque control capability. The simulation results not only verified the effectiveness of IBKA in ADRC parameter optimization but also demonstrated the potential of ADRC in improving PMSM control performance. [Conclusion] The control strategy proposed in this paper provides an effective solution for PMSM in high precision, high dynamic, and high anti-interference applications, with important theoretical significance and practical value.