This paper presents an Enhanced Whale Optimization Algorithm (EWO) approach for tuning to perfection of Fractional Order Proportional Integral and integral order Controller (FOPI λ ) is used to sensorless speed control of permanent magnet Brushless DC (PMBLDC) motor under the operating dynamic condition such as (i) speed change by set speed command signal (ii) varying load conditions, (iii) integrated conditions and (iv) controller parameters uncertainty. On the other hand, it deals with a reduced THD (Total Harmonic Distortion) under dynamic operating conditions to improve the power quality for the above control system. Here present are three optimization techniques, namely (i) Enhanced Whale Optimization (EWO), (ii) Invasive Weed Optimization (IWO), and (iii) Social Spider Optimization (SSO) for fine-tuning of the FOPI λ controller parameters with reduction of THD. The proposed optimization algorithm optimized FOPI λ controller are compared under various BLDC motor operating conditions. Based on the results of MATLAB/Simulink models, the proposed algorithms are evaluated. Here, both the simulation and the results of the experiments are validated for the proposed controller technique. It demonstrates that the effectiveness of the proposed controllers is completely validated by comparing the three intelligent optimization techniques mentioned above. The EWO optimized FOPI λ controller for speed control of sensorless PMBLDC motor clearly outperforms the other two intelligent controllers by minimizing the time domain parameters, THD, performance Indices error, convergence time, control efforts, cost function, mean and standard deviation.

中文翻译：

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基于增强型鲸鱼优化分数阶 pi λ 控制器的无传感器无刷直流电机在动态运行条件下的电能质量改进

本文提出了一种用于优化分数阶比例积分和积分阶控制器 (FOPI λ) 的增强型鲸鱼优化算法 (EWO) 方法，用于在运行动态条件下对永磁无刷直流 (PMBLDC) 电机进行无传感器速度控制，例如作为 (i) 速度由设定的速度指令信号 (ii) 变化的负载条件、(iii) 综合条件和 (iv) 控制器参数不确定性引起的速度变化。另一方面，它在动态运行条件下处理降低的 THD（总谐波失真），以改善上述控制系统的电能质量。这里介绍了三种优化技术，即（i）增强型鲸鱼优化（EWO），（ii）入侵杂草优化（IWO），(iii) 社交蜘蛛优化 (SSO)，用于微调 FOPI λ 控制器参数并降低 THD。所提出的优化算法优化了 FOPI λ 控制器在各种 BLDC 电机运行条件下进行了比较。基于 MATLAB/Simulink 模型的结果，对所提出的算法进行了评估。在这里，仿真和实验结果都针对所提出的控制器技术进行了验证。通过比较上述三种智能优化技术，表明所提出的控制器的有效性得到了完全验证。用于无传感器 PMBLDC 电机速度控制的 EWO 优化 FOPI λ 控制器通过最小化时域参数、THD、性能指标误差、收敛时间、控制工作、