This paper proposes a new hybrid novel optimization approach, called Enhanced Artificial Bee Colony Algorithm (EABC) for designing an optimal PI controller for single-phase Shunt Active Power Filter (SAPF). The proposed EABC algorithm optimizes the gain values of the PI controller to improve the dynamic performance of SAPF. In this EABC, the adaptive real coded genetic algorithm (ARGA) is integrated with the Artificial Bee Colony (ABC) algorithm and this integration improves the exploration and exploitation ABC and speed up the convergence rate. The minimization of integral square error (ISE) is considered as an objective function to manipulate the gain values of the PI controller. The system tested with MATLAB simulation results are implemented in the hardware circuit with the same set of parameters. The proposed hardware system is designed with the Cyclone-IV EP4CE30F484 FPGA controller and the gain value for this proposed controller is fed from the simulation results tested with ABC and EABC algorithm. The results obtained from the hardware setup is compared with simulation results. The experimental result enhanced the performance of THD of source current, settling time and percentage peak overshoot of DC Link voltage.

中文翻译：

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单相并联有源滤波器增强型人工蜂群算法优化PI控制算法的实时实现与分析

本文提出了一种新的混合新颖优化方法，称为增强人工蜂群算法 (EABC)，用于设计单相并联有源滤波器 (SAPF) 的最佳 PI 控制器。提出的 EABC 算法优化了 PI 控制器的增益值，以提高 SAPF 的动态性能。在该 EABC 中，自适应实数编码遗传算法（ARGA）与人工蜂群（ABC）算法相结合，这种集成改进了探索和开发 ABC，加快了收敛速度。积分平方误差 (ISE) 的最小化被视为操纵 PI 控制器增益值的目标函数。用MATLAB仿真结果测试的系统在具有相同参数集的硬件电路中实现。建议的硬件系统采用 Cyclone-IV EP4CE30F484 FPGA 控制器设计，该控制器的增益值来自使用 ABC 和 EABC 算法测试的仿真结果。将从硬件设置获得的结果与仿真结果进行比较。实验结果提高了源电流的 THD、建立时间和直流链路电压峰值过冲百分比的性能。