• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于群体启发算法的升压变换器倾斜积分微分控制器的优化设计

Optimal design of tilt integral derivative controller for a boost converter based on swarm-inspired algorithms.

作者信息

Mukhtar Adnan, Tiwari Pyare Mohan, Alotaibi Saud, Alzahrani Thabet, Namomsa Borchala, Ahmed Mahrous

机构信息

Department of Electrical and Electronics Engineering, Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India.

Electrical Engineering Department, College of Engineering, Shaqra University, Al Duwadimi, 11911, Riyadh, Saudi Arabia.

出版信息

Sci Rep. 2025 Jan 2;15(1):57. doi: 10.1038/s41598-024-84088-7.

DOI:10.1038/s41598-024-84088-7
PMID:39747248
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11697515/
Abstract

This article proposes a novel dual-loop control (DLC) method with a Tilt Integral Derivative (TID) Controller for output voltage regulation and inductor current regulation in a boost converter. The TID controller is designed with the aid of swarm inspired algorithms, particularly Artificial Bee Colony (ABC) and Salp Swarm Optimization (SSO). The TID Controller is a robust, and feedback type of controller and belongs to the family of fractional order controllers. This controller has several advantages, such as superior control over complex systems, improved disturbance rejection, enhanced robustness, and better transient response over conventional controllers, such as, PID. Due to the inherent instability and limited controllability, a boost converter may pose significant challenges, necessitating the use of sophisticated control methodologies. The DLC method being proposed comprises of an inner-loop for current regulation and an outer-loop for voltage regulation. The inner-loop comprises of a current sensor and a TID controller, which provide a fast transient response and overcurrent protection, while as the outer-loop comprises of a voltage sensor and a TID controller, which ensure a precise steady-state accuracy and output voltage regulation. The utilization of ABC and SSO techniques effectively address the specific challenges associated with boost converters, leading to enhanced stability and transient response. The proposed control method demonstrates efficacy through extensive simulation and experimental investigation under start-up response, step perturbations in external load, and reference voltage change. The experimentation is conducted on a laboratory prototype using dspace DS1104 control board with MPC8240 processor. The system demonstrates improved time domain specifications, with settling time of 10 ms and 6 ms during start-up, 5 ms and 4.5 ms, during load change, 6 ms and 4.5 ms during reference voltage change for output voltage and inductor current respectively under the action of SSO-based TID controller. This article presents the first documented application and development of ABC and SSO-optimized TID controllers. However, these algorithms have shown promise in other engineering applications, which suggests that they may be effective in optimizing output voltage and inductor current in boost converters as well. This research enhances the control of boost converters, making them more suitable for a range of applications in power supply, EVs, green energy systems, and battery charging.

摘要

本文提出了一种新颖的双环控制(DLC)方法,该方法采用倾斜积分微分(TID)控制器来调节升压变换器的输出电压和电感电流。TID控制器是借助群体启发算法设计的,特别是人工蜂群(ABC)算法和鹈鹕群优化(SSO)算法。TID控制器是一种鲁棒的反馈型控制器,属于分数阶控制器家族。该控制器具有多个优点,例如对复杂系统具有卓越的控制能力、改进的抗干扰能力、增强的鲁棒性以及相较于传统控制器(如PID控制器)更好的瞬态响应。由于升压变换器固有的不稳定性和有限的可控性,可能会带来重大挑战,因此需要使用复杂的控制方法。所提出的DLC方法包括用于电流调节的内环和用于电压调节的外环。内环由电流传感器和TID控制器组成,可提供快速瞬态响应和过流保护,而外环由电压传感器和TID控制器组成,可确保精确的稳态精度和输出电压调节。ABC和SSO技术的应用有效地解决了与升压变换器相关的特定挑战,从而提高了稳定性和瞬态响应。通过在启动响应、外部负载的阶跃扰动以及参考电压变化情况下进行广泛的仿真和实验研究,验证了所提出控制方法的有效性。实验是在一个使用带有MPC8240处理器的dspace DS1104控制板的实验室原型上进行的。在基于SSO的TID控制器作用下,系统在输出电压和电感电流方面展示了改进的时域指标,启动期间的调节时间分别为10毫秒和6毫秒,负载变化期间为5毫秒和4.5毫秒,参考电压变化期间为6毫秒和4.5毫秒。本文介绍了ABC和SSO优化的TID控制器的首次文献记载的应用和开发。然而,这些算法在其他工程应用中已显示出前景,这表明它们在优化升压变换器的输出电压和电感电流方面也可能有效。这项研究增强了对升压变换器的控制,使其更适合在电源、电动汽车、绿色能源系统和电池充电等一系列应用中使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/6fd760128133/41598_2024_84088_Fig21_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/dd4c218e3ba5/41598_2024_84088_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/1d83280ccba1/41598_2024_84088_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/3f4619ded0de/41598_2024_84088_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/9383b3a7e132/41598_2024_84088_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/6bb823b6e4e2/41598_2024_84088_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/891454cd2c9d/41598_2024_84088_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/a19b618e3049/41598_2024_84088_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/c1ec7558614c/41598_2024_84088_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/ef790fdbd098/41598_2024_84088_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/1bef8d084733/41598_2024_84088_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/25a7d7baaa57/41598_2024_84088_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/e9699587d25e/41598_2024_84088_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/928fb44f294b/41598_2024_84088_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/feb9413c6607/41598_2024_84088_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/16d5faedc1d9/41598_2024_84088_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/5feaf89dba6d/41598_2024_84088_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/9c2a93c511ef/41598_2024_84088_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/12e7a2e4519a/41598_2024_84088_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/bf705cbbce40/41598_2024_84088_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/00c4960ad2ce/41598_2024_84088_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/6fd760128133/41598_2024_84088_Fig21_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/dd4c218e3ba5/41598_2024_84088_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/1d83280ccba1/41598_2024_84088_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/3f4619ded0de/41598_2024_84088_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/9383b3a7e132/41598_2024_84088_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/6bb823b6e4e2/41598_2024_84088_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/891454cd2c9d/41598_2024_84088_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/a19b618e3049/41598_2024_84088_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/c1ec7558614c/41598_2024_84088_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/ef790fdbd098/41598_2024_84088_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/1bef8d084733/41598_2024_84088_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/25a7d7baaa57/41598_2024_84088_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/e9699587d25e/41598_2024_84088_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/928fb44f294b/41598_2024_84088_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/feb9413c6607/41598_2024_84088_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/16d5faedc1d9/41598_2024_84088_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/5feaf89dba6d/41598_2024_84088_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/9c2a93c511ef/41598_2024_84088_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/12e7a2e4519a/41598_2024_84088_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/bf705cbbce40/41598_2024_84088_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/00c4960ad2ce/41598_2024_84088_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b39/11697515/6fd760128133/41598_2024_84088_Fig21_HTML.jpg

相似文献

1
Optimal design of tilt integral derivative controller for a boost converter based on swarm-inspired algorithms.基于群体启发算法的升压变换器倾斜积分微分控制器的优化设计
Sci Rep. 2025 Jan 2;15(1):57. doi: 10.1038/s41598-024-84088-7.
2
A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system.一种在电力市场放开的混合电力系统下采用浣熊优化算法调谐的新型TID+IDN控制器。
Sci Rep. 2025 Feb 9;15(1):4838. doi: 10.1038/s41598-025-89237-0.
3
Performance comparison between PID and Fuzzy logic controllers for the hardware implementation of traditional high voltage DC-DC boost converter.用于传统高压DC-DC升压转换器硬件实现的PID控制器与模糊逻辑控制器的性能比较。
Heliyon. 2024 Aug 22;10(17):e36750. doi: 10.1016/j.heliyon.2024.e36750. eCollection 2024 Sep 15.
4
Performance analysis of DC-DC Buck converter with innovative multi-stage PIDn(1+PD) controller using GEO algorithm.采用GEO算法的创新型多级PIDn(1+PD)控制器的DC-DC降压变换器性能分析
Sci Rep. 2024 Oct 27;14(1):25612. doi: 10.1038/s41598-024-77395-6.
5
MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink.基于新型混合粒子群优化算法和樽海鞘群优化算法的最大功率点跟踪(MPPT)机制,用于通过Simulink进行电池充电
Sci Rep. 2022 Feb 17;12(1):2664. doi: 10.1038/s41598-022-06609-6.
6
Enhancing disturbance rejection in boost converter for CPL: A controller design approach with partial pole placement and approximate model matching.
ISA Trans. 2025 Jan;156:389-400. doi: 10.1016/j.isatra.2024.10.023. Epub 2024 Oct 28.
7
Hybrid dual-area power grid frequency fluctuation effective control utilizing a maiden combination of MOA-based 1 + PIID and PDF controllers.利用基于金属氧化物避雷器的1+PIID和概率密度函数(PDF)控制器的首次组合实现混合双区域电网频率波动的有效控制
Sci Prog. 2025 Jan-Mar;108(1):368504251330521. doi: 10.1177/00368504251330521. Epub 2025 Mar 28.
8
Fractional-Order Approximation of PID Controller for Buck-Boost Converters.Buck-Boost变换器的PID控制器的分数阶近似
Micromachines (Basel). 2021 May 21;12(6):591. doi: 10.3390/mi12060591.
9
Full state observer-based pole placement controller for pulse width modulation switched mode voltage-controlled buck Converter.用于脉宽调制开关模式电压控制降压变换器的基于全状态观测器的极点配置控制器。
Heliyon. 2024 May 4;10(9):e30662. doi: 10.1016/j.heliyon.2024.e30662. eCollection 2024 May 15.
10
Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm.基于具有模式搜索算法的创新型蛇优化器的非理想降压变换器的抗干扰PID-FF控制器设计
Heliyon. 2024 Jul 14;10(14):e34448. doi: 10.1016/j.heliyon.2024.e34448. eCollection 2024 Jul 30.