Robust H∞ control for LFC of discrete T–S fuzzy MAPS with DFIG and time-varying delays

IF 2.1 2区数学 Q1 MATHEMATICS, APPLIED

Journal of Computational and Applied Mathematics Pub Date : 2024-09-18 DOI:10.1016/j.cam.2024.116271

Zixiang Shen, Guo Chen

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引用次数: 0

Abstract

The

H_{\infty}

LFC control problem for a class of nonlinear power systems with time-varying delays is under study. Considering uncertainties arising from nonlinear issues such as the generation rate constraint (GRC) and governor dead band (GDB), as well as the high variability of renewable energy sources like wind power, the model is transformed into a discrete-time Takagi–Sugeno (T–S) fuzzy model with parameter uncertainty. By constructing a Lyapunov–Krasovskii functional, and employing difference inequalities and generalized cross-convex matrix inequalities, sufficient conditions for the asymptotic stability of power systems are provided. Based on the obtained conditions, a controller is designed to ensure the asymptotic stability of Multi-Area Power Systems (MAPS), with the performance index being

H_{\infty}

. Finally, simulation results demonstrate the correctness and effectiveness of the theorem.

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带双馈变流器和时变延迟的离散 T-S 模糊 MAPS LFC 的鲁棒 H∞ 控制

我们正在研究一类具有时变延迟的非线性电力系统的 H∞ LFC 控制问题。考虑到发电率约束（GRC）和调速器死区（GDB）等非线性问题所产生的不确定性，以及风电等可再生能源的高变化性，该模型被转化为具有参数不确定性的离散时间高木-菅野（T-S）模糊模型。通过构建 Lyapunov-Krasovskii 函数，并利用差分不等式和广义交叉凸矩阵不等式，提供了电力系统渐近稳定性的充分条件。根据所获得的条件，设计了一种控制器来确保多区域电力系统（MAPS）的渐近稳定性，其性能指标为 H∞。最后，仿真结果证明了定理的正确性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Applied Mathematics 数学-应用数学

CiteScore

5.40

自引率

4.20%

发文量

437

审稿时长

3.0 months

期刊介绍： The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.