利用基于 Aquila 优化器的 PID 控制器实现 FSBB 转换器的优化控制

IF 3 3区 工程技术 Q2 CHEMISTRY, ANALYTICAL Micromachines Pub Date : 2024-10-21 DOI:10.3390/mi15101277
Luoyao Ren, Dazhi Wang, Yupeng Zhang
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引用次数: 0

摘要

本文介绍了一种为四开关降压-升压(FSBB)转换器确定 PID 控制器最佳系数的新方法。这项研究的主要目的是利用新开发的 Aquila 优化器 (AO) 微调 PID 控制器的参数,从而提高 FSBB 转换器的性能。PID 控制器因其在 FSBB 转换器中简单而有效的控制而得到广泛认可。然而,为了进一步提高控制系统的效率和可靠性,必须对 PID 控制参数进行优化。在这种情况下,AO 算法的应用被证明是一项重大进步。通过优化 PID 系数,可以提高系统的动态响应能力,从而缩短响应时间。此外,控制系统的鲁棒性也得到了增强,这对于确保在不同条件下稳定可靠地运行至关重要。在保持系统稳定性和确保控制系统在具有挑战性的条件下正常运行方面,AO 的使用发挥了关键作用。为了证明所提方法的有效性和潜力,在相同的测试环境下,将经过 AO 优化的 PID 控制器的性能与经过其他优化算法调整的 PID 控制器的性能进行了比较。结果表明,AO 在动态响应和鲁棒性方面优于其他优化算法,从而验证了所提方法的效率和正确性。这项工作凸显了在 FSBB 转换器的 PID 调节中使用 Aquila 优化器的优势,为提高系统性能提供了一个前景广阔的解决方案。
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Optimal Control of FSBB Converter with Aquila Optimizer-Based PID Controller.

This paper presents a new methodology for determining the optimal coefficients of a PID controller for a four-switch buck-boost (FSBB) converter. The main objective of this research is to improve the performance of FSBB converters by fine-tuning the parameters of the PID controller using the newly developed Aquila Optimizer (AO). PID controllers are widely recognized for their simple yet effective control in FSBB converters. However, to further improve the efficiency and reliability of the control system, the PID control parameters must be optimized. In this context, the application of the AO algorithm proves to be a significant advance. By optimizing the PID coefficients, the dynamic responsiveness of the system can be improved, thus reducing the response time. In addition, the robustness of the control system is enhanced, which is essential to ensure stable and reliable operation under varying conditions. The use of AOs plays a key role in maintaining system stability and ensuring the proper operation of the control system even under challenging conditions. In order to demonstrate the effectiveness and potential of the proposed method, the performance of the AO-optimized PID controller was compared with that of PID controllers tuned by other optimization algorithms in the same test environment. The results show that the AO outperforms the other optimization algorithms in terms of dynamic response and robustness, thus validating the efficiency and correctness of the proposed method. This work highlights the advantages of using the Aquila Optimizer in the PID tuning of FSBB converters, providing a promising solution for improving system performance.

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来源期刊
Micromachines
Micromachines NANOSCIENCE & NANOTECHNOLOGY-INSTRUMENTS & INSTRUMENTATION
CiteScore
5.20
自引率
14.70%
发文量
1862
审稿时长
16.31 days
期刊介绍: Micromachines (ISSN 2072-666X) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to micro-scaled machines and micromachinery. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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