| 张冰战,虎啸鸣,李传宝,方涛,毕楗波,赵晓敏.改进 HHO 在无刷直流电机转速控制中的应用[J].电子测量与仪器学报,2026,40(4):79-88 |
| 改进 HHO 在无刷直流电机转速控制中的应用 |
| Application of enhanced HHO in speed control of brushless DC motor |
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| DOI： |
| 中文关键词: 改进哈里斯鹰算法 直流无刷电机控制 对立学习 自适应权重 平滑处理 非线性能量因子 |
| 英文关键词:enhanced HHO BLDC control opposition-based learning adaptive weights smoothing technique nonlinear energy factor |
| 基金项目:安徽省科技攻坚计划项目（重大专项）（202423e12050001）、国家自然科学基金(5247120260)项目资助 |
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| Author | Institution |
| Zhang Bingzhan | 1.School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009,China;
2.Anhui Key Laboratory of Digital Design and Manufacturing, Hefei University of Technology, Hefei 230009,China |
| Hu Xiaoming | School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009,China |
| Li Chuanbao | Hefei Longkong Intelligent Technology Co. Ltd., Hefei 230600,China |
| Fang Tao | School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009,China |
| Bi Jianbo | School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009,China |
| Zhao Xiaomin | School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009,China |
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| 中文摘要: |
| 随着工业电动化和自动化水平的提升,电机作为动力系统的核心部件,其运行效率与控制性能直接影响系统的整体性能和可靠性。传统PI控制器由于响应速度较慢,抗扰能力不足,常常难以满足高动态控制需求。针对这一问题,提出了一种基于改进哈里斯鹰优化算法与PI控制器相结合的无刷直流电机转速控制方法。该方法结合了对立学习,自适应权重,非线性能量因子和嵌入式平滑处理等机制,显著提升了优化搜索能力和精度,并增强了控制系统在动态工况下的适应性。通过在Simulink仿真环境中进行多种工况测试,并结合基于GD32F103RCT6控制平台的实机试验,对比分析了EHHO PI与传统PI控制方法在突加速度,突加负载和变速变载等复杂工况下的控制性能。结果表明,EHHO-PI控制器在速度响应,抗扰动能力,调节精度等方面均优于传统控制策略,表现出较强的鲁棒性和实用性,适用于各种复杂环境下的稳定控制。该控制策略为电机控制技术提供了一种有效的优化方案,具有广泛的工程应用前景。 |
| 英文摘要: |
| With the advancement of industrial electrification and automation, electric motors, as the core components of power systems, directly influence the overall performance and reliability of the system. Traditional PI controllers often fail to meet high-dynamic control demands due to their slow response speed and poor disturbance rejection capability. To address this issue, this paper proposes a speed control method for brushless DC motors that integrates an enhanced Harris hawks optimization (EHHO) algorithm with a PI controller. The proposed method incorporates opposition-based learning, adaptive weights, nonlinear energy factors, and embedded smoothing techniques, significantly improving the optimization search capability and accuracy while enhancing the control system’s adaptability to dynamic operating conditions. Through Simulink simulations and hardware experiments based on a GD32F103RCT6 control platform, the performance of EHHO-PI is compared with that of traditional PI control in various complex conditions, including sudden acceleration, sudden load, and variable speed/load scenarios. The results demonstrate that the EHHO-PI controller outperforms the conventional methods in terms of speed response, disturbance rejection, and regulation accuracy, showing strong robustness and practical applicability. This control strategy provides an effective optimization solution for motor control technology with broad engineering application prospects. |
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