Data-driven predictive control of perturbed buck converters using a modified iterative feedback tuning algorithm

IF 1.7 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Kamran Moradi, Pourya Zamani, Qobad Shafiee
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引用次数: 0

Abstract

The most challenging aspect of utilizing model predictive controllers (MPCs), particularly those involving power electronic applications, is the extraction of a model that accurately represents the behavior of the studied system. Concerning the use of power electronic applications, as long as an MPC is used, adjusting the controller parameters brings difficulties. In addition, as the number of elements increases, it becomes harder to get the best control law out of the model. To do away with the need for model extraction, this study presents an offline data-driven approach in conjunction with the MPC that can optimally adjust the MPC parameters based on the iterative feedback tuning (IFT) algorithm called the iterative feedback predictive controller (IFPC). The proposed method eliminates concerns regarding selecting an optimal number of algorithm iterations, thereby reducing operating costs, by introducing a modified IFT called feedback-based IFPC (FIFPC) while simultaneously achieving optimal MPC parameters. The proposed method is applied to a constant voltage load (CVL) connected less-than-ideal buck converter, that is, one with perturbed filter elements and variable loads. A robust stability analysis (RSA) is performed under normal operating conditions to investigate the robustness behavior of the proposed controller. Simulation studies are presented to evaluate the proposed controller under different scenarios, such as step and abrupt load changes and measurement noise, compared with the well-known model-based and data-enabled predictive controller (DeePC) approaches in the MATLAB/Simulink environment.

Abstract Image

使用改进的迭代反馈调整算法对受扰动降压转换器进行数据驱动的预测控制
使用模型预测控制器(MPC),尤其是涉及电力电子应用的模型预测控制器,最大的挑战在于如何提取能准确代表所研究系统行为的模型。就电力电子应用而言,只要使用 MPC,调整控制器参数就会带来困难。此外,随着元素数量的增加,从模型中获得最佳控制法则也变得更加困难。为了消除模型提取的需要,本研究提出了一种与 MPC 结合使用的离线数据驱动方法,该方法可根据称为迭代反馈预测控制器(IFPC)的迭代反馈调整(IFT)算法优化调整 MPC 参数。通过引入一种称为基于反馈的迭代反馈预测控制器(FIFPC)的改进型 IFT,同时实现最佳 MPC 参数,所提出的方法消除了选择最佳算法迭代次数的顾虑,从而降低了运行成本。所提出的方法适用于与恒压负载(CVL)连接的非理想降压转换器,即具有扰动滤波器元件和可变负载的转换器。在正常运行条件下进行了鲁棒稳定性分析 (RSA),以研究拟议控制器的鲁棒性。在 MATLAB/Simulink 环境中进行了仿真研究,以评估拟议控制器在阶跃和突然负载变化以及测量噪声等不同情况下与著名的基于模型和数据支持的预测控制器 (DeePC) 方法的比较。
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来源期刊
IET Power Electronics
IET Power Electronics ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
5.50
自引率
10.00%
发文量
195
审稿时长
5.1 months
期刊介绍: IET Power Electronics aims to attract original research papers, short communications, review articles and power electronics related educational studies. The scope covers applications and technologies in the field of power electronics with special focus on cost-effective, efficient, power dense, environmental friendly and robust solutions, which includes: Applications: Electric drives/generators, renewable energy, industrial and consumable applications (including lighting, welding, heating, sub-sea applications, drilling and others), medical and military apparatus, utility applications, transport and space application, energy harvesting, telecommunications, energy storage management systems, home appliances. Technologies: Circuits: all type of converter topologies for low and high power applications including but not limited to: inverter, rectifier, dc/dc converter, power supplies, UPS, ac/ac converter, resonant converter, high frequency converter, hybrid converter, multilevel converter, power factor correction circuits and other advanced topologies. Components and Materials: switching devices and their control, inductors, sensors, transformers, capacitors, resistors, thermal management, filters, fuses and protection elements and other novel low-cost efficient components/materials. Control: techniques for controlling, analysing, modelling and/or simulation of power electronics circuits and complete power electronics systems. Design/Manufacturing/Testing: new multi-domain modelling, assembling and packaging technologies, advanced testing techniques. Environmental Impact: Electromagnetic Interference (EMI) reduction techniques, Electromagnetic Compatibility (EMC), limiting acoustic noise and vibration, recycling techniques, use of non-rare material. Education: teaching methods, programme and course design, use of technology in power electronics teaching, virtual laboratory and e-learning and fields within the scope of interest. Special Issues. Current Call for papers: Harmonic Mitigation Techniques and Grid Robustness in Power Electronic-Based Power Systems - https://digital-library.theiet.org/files/IET_PEL_CFP_HMTGRPEPS.pdf
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