用于感应加热应用的基于自调整模糊控制的双输入九电平自平衡开关电容器逆变器

IF 1.5 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Manish Kurre, Priyankar Roy, Atanu Banerjee
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引用次数: 0

摘要

本文针对感应加热(IH)应用,提出了一种基于精简元件双输入九电平开关电容多电平逆变器的自调整智能模糊逻辑控制器(STIFLC)。此外,为了生成曲线,本研究采用了曲线生成器,将上升时间和目标温度的设置作为模糊逻辑控制器(FLC)的反馈参考。为了实现这一目标,必须根据系统要求固定 FLC 中的不同量化因子。为了解决这个问题,我们对所有量化因子进行了精确分析,并设计了 STIFLC,它能够控制感应加热温度,并能在实时情况下运行。此外,还比较了传统 FLC 和 STIFLC 的控制性能,并得出了决定系统效率的功率损耗方程。最后,对包括 IH 系统在内的 5kVA 逆变器原型进行了模拟和实验测试,以确认所提系统的有效性。研究结果表明,包含多电平逆变器的 STIFLC 能显著提高控制器的适应性和控制能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Self Tuning Fuzzy Control Based Dual Input Nine-Level Self Balancing Switched-Capacitor Inverter for Induction Heating Applications

A Self Tuning Fuzzy Control Based Dual Input Nine-Level Self Balancing Switched-Capacitor Inverter for Induction Heating Applications

This paper proposes a self tuning intelligent fuzzy logic controller (STIFLC) based reduced component dual input nine-level switched-capacitor multilevel inverter for induction heating (IH) applications. Moreover, to generate the curve producer referring to setting of rise time along with target temperature as being a feedback reference to the fuzzy logic controller (FLC) is adopted in this work. To acquire this goal different quantization factors in FLC must be fixed as per the system requirement. To address this drawback all the quantization factors are analysed precisely and STIFLC is designed which is capable for controlling the induction heating temperature and to perform in real time situation. Additionally, the control performance of traditional FLC and STIFLC is compared and power loss equations are derived which determines the system efficiency. Finally, simulation and experimental tests were carried out on a 5kVA inverter prototype including the IH system to confirm the potency of the proposed system. The findings demonstrate particularly the proposed STIFLC including multilevel inverter significantly increased the controllers adaptability and control capacity.

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来源期刊
CiteScore
5.50
自引率
4.20%
发文量
93
审稿时长
>12 weeks
期刊介绍: Transactions of Electrical Engineering is to foster the growth of scientific research in all branches of electrical engineering and its related grounds and to provide a medium by means of which the fruits of these researches may be brought to the attentionof the world’s scientific communities. The journal has the focus on the frontier topics in the theoretical, mathematical, numerical, experimental and scientific developments in electrical engineering as well as applications of established techniques to new domains in various electical engineering disciplines such as: Bio electric, Bio mechanics, Bio instrument, Microwaves, Wave Propagation, Communication Theory, Channel Estimation, radar & sonar system, Signal Processing, image processing, Artificial Neural Networks, Data Mining and Machine Learning, Fuzzy Logic and Systems, Fuzzy Control, Optimal & Robust ControlNavigation & Estimation Theory, Power Electronics & Drives, Power Generation & Management The editors will welcome papers from all professors and researchers from universities, research centers, organizations, companies and industries from all over the world in the hope that this will advance the scientific standards of the journal and provide a channel of communication between Iranian Scholars and their colleague in other parts of the world.
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