Ersali Cihan, Hekimoglu Baran, Yilmaz Musa, Martinez-Morales Alfredo A, Akinci Tahir Cetin
Department of Electrical and Electronics Engineering, Batman University, Batman, 72100, Turkey.
Bourns College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92521, USA.
Heliyon. 2024 Jul 14;10(14):e34448. doi: 10.1016/j.heliyon.2024.e34448. eCollection 2024 Jul 30.
The optimal design of a proportional-integral-derivative controller with two cascaded first-order low-pass filters (PID-FF) for non-ideal buck converters faces significant challenges, including effective disturbance rejection, robustness to parameter variations, and the mitigation of high-frequency signal noise, with existing approaches often struggling and leading to suboptimal performance in practical applications. This study addresses these challenges by introducing a constraint on the open-loop crossover frequency to mitigate high-frequency noise and ensuring the controller prioritizes maintaining constant output voltage and robust responsiveness to input voltage and load current variations. This study also introduces an innovative metaheuristic algorithm, the opposition-based snake optimizer with pattern search (OSOPS), designed to address these limitations. OSOPS enhances the Snake Optimizer (SO) by integrating opposition-based learning (OBL) and Pattern Search (PS), thereby improving its exploration and exploitation capabilities. The proposed algorithm design includes a crossover frequency constraint aimed at counteracting high-frequency noise and ensuring robust performance under diverse disturbances. The efficacy of the OSOPS algorithm is demonstrated through rigorous statistical box plot analysis and convergence response comparisons with the original SO algorithm. Additionally, we systematically compare the performance of the OSOPS-based PID-FF-controlled non-ideal buck converter system against systems utilizing the original SO algorithm and the classical pole placement (PP) method. This evaluation encompasses transient and frequency responses, disturbance rejection, and robustness analysis. The results reveal that the OSOPS-based system outperforms the SO- and PP-based systems with 14.21 % and 32.10 % faster rise times, along with 15.38 % and 84.95 % faster settling times, respectively. The OSOPS and SO systems also exhibit higher bandwidths, exceeding the PP-based system by 18.74 % and 17.03 %, respectively. By addressing the key challenges in PID-FF controller design for non-ideal buck converters, this study provides a substantial advancement in control strategy, promising enhanced performance in practical applications.
为非理想降压变换器设计带有两个级联一阶低通滤波器的比例积分微分控制器（PID-FF）的最优设计面临重大挑战，包括有效抑制干扰、对参数变化的鲁棒性以及减轻高频信号噪声，现有方法在实际应用中常常难以应对，导致性能欠佳。本研究通过对开环交叉频率引入约束来减轻高频噪声，并确保控制器优先维持恒定输出电压以及对输入电压和负载电流变化具有鲁棒响应，从而应对这些挑战。本研究还引入了一种创新的元启发式算法，即基于对立学习和模式搜索的蛇优化器（OSOPS），旨在解决这些局限性。OSOPS通过集成基于对立学习（OBL）和模式搜索（PS）来增强蛇优化器（SO），从而提高其探索和利用能力。所提出的算法设计包括一个交叉频率约束，旨在抵消高频噪声并确保在各种干扰下具有鲁棒性能。通过严格的统计箱线图分析以及与原始SO算法的收敛响应比较，证明了OSOPS算法的有效性。此外，我们系统地比较了基于OSOPS的PID-FF控制的非理想降压变换器系统与使用原始SO算法和经典极点配置（PP）方法的系统的性能。该评估包括瞬态和频率响应以及抗干扰和鲁棒性分析。结果表明，基于OSOPS的系统的上升时间分别比基于SO和PP的系统快14.21%和32.10%，稳定时间分别快15.38%和84.95%。OSOPS和SO系统还具有更高的带宽，分别比基于PP的系统高出18.74%和17.03%。通过解决非理想降压变换器PID-FF控制器设计中的关键挑战，本研究在控制策略方面取得了重大进展，有望在实际应用中实现更高的性能。
