【目的】永磁同步电机(PMSM)因其高功率密度、高效率等优势在工业中广泛应用。然而传统控制方法在面对系统参数改变和外部扰动时，存在控制性能下降的问题。本文提出一种基于海洋捕食者算法(MPA)优化的滑模变结构控制(SMVSC)策略，旨在增强系统的鲁棒性和稳态精度。【方法】首先，在PMSM的矢量控制框架中，将转速外环的传统比例积分控制器替换为SMVSC控制器，利用SMVSC的强鲁棒性抑制系统参数变化和外部扰动的影响。随后，采用双幂次趋近律进一步改进SMVSC，在趋近滑模面初期采用高增益加速收敛，后期切换为低增益抑制抖振，兼顾动态响应速度与控制平滑性。同时引入MPA对SMVSC趋近律系数、滑模面参数进行优化，避免局部最优，确保控制器参数适用于不同工况需求。最后，通过Matlab/Simulink搭建PMSM调速系统仿真模型，同时在实验平台上开展试验，验证所提方法的有效性。【结果】仿真和试验结果表明，经过MPA优化的双幂次趋近律SMVSC提升了PMSM的调速性能，使系统的稳定性及鲁棒性得到有效改善，超调量与调节时间缩短。与传统控制方法相比，优化后的控制器在不同的工况下表现出良好的动态响应能力，验证了所提方法的有效性。【结论】本文提出的基于MPA优化的双幂次趋近律SMVSC策略，能够有效提升PMSM在参数变化和外部负载扰动下的控制性能，为PMSM的高性能控制提供了新的解决方案。

[Objective] Permanent magnet synchronous motor (PMSM) is widely adopted in industrial applications due to their high power density, superior efficiency, and excellent dynamic performance. However, conventional control strategies, often exhibit degraded performance when confronted with system parameter variations and external disturbances. To address these challenges, this paper proposes a novel sliding mode variable structure control (SMVSC) strategy optimized by the marine predators algorithm (MPA), aiming to enhance system robustness and steady-state accuracy. [Methods] Within the vector control framework of PMSM, the conventional proportional integral controller in the speed outer loop was replaced with SMVSC controller. The inherent robustness of SMVSC was leveraged to mitigate the adverse effects of parameter uncertainties and external disturbances. To further refine the SMVSC design, a double-power reaching law was introduced to optimize the approaching process. During the initial phase of converging to the sliding mode surface, a high gain was employed to accelerate convergence speed. Subsequently, the gain was dynamically reduced in the later phase to suppress chattering phenomena, thereby balancing rapid dynamic response with control smoothness. Additionally, the MPA was utilized to optimize critical parameters of the SMVSC, including reaching rate coefficients and sliding surface parameters, avoided local optima and ensures the adaptability of controller parameters under diverse operating conditions. Finally, the simulation model of PMSM speed regulation system was built by Matlab/Simulink, and experiments were carried out on the physical platform, verified the effectiveness of the proposed method. [Results] Simulation and experimental results showed that the MPA-optimized double-power reaching law SMVSC significantly improves PMSM speed regulation performance, with enhanced stability, reduced overshoot, and shorter settling time. Compared to traditional methods, the optimized controller exhibits superior dynamic response and robustness under varying conditions. [Conclusion] The proposed MPA-optimized SMVSC strategy effectively enhances PMSM control performance under parameter uncertainties and external disturbances, offering a new solution for high-performance of PMSM.

国家自然科学基金(62163006,52267003);贵州省科技厅支撑计划项目(QKHZ[2023]G179)