Prescribed Performance Control of Two-Time-Scale Systems and Its Application

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Ze-Hong Zeng, Yan-Wu Wang, Xiao-Kang Liu, Wu Yang
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引用次数: 0

Abstract

This article explores the prescribed performance control design for linear two-time-scale systems (TTSSs). Due to ill-conditioning and high dimensionality, existing prescribed performance control methods for single-time-scale systems are unsuitable for TTSSs. Moreover, current TTSS methodologies focus on steady-state performance, often neglecting transient dynamics. To address these challenges, we first apply the Chang transformation to decouple the fast and slow states. Next, we use a state transformation to convert the state equation into block form to eliminate the requirement of a full row-rank input matrix. Finally, the backstepping method is utilized to design the prescribed performance control. The effectiveness and advantages of the proposed control strategy are demonstrated through two examples: a numerical simulation and a hardware-in-the-loop experiment involving an electronic circuit system.

双时间尺度系统的规定性能控制及其应用
本文探讨线性双时间尺度系统(ttss)的规定性能控制设计。由于单时间尺度系统的病态和高维性,现有规定的单时间尺度系统性能控制方法不适用于ttss。此外,目前的TTSS方法侧重于稳态性能,往往忽略了瞬态动力学。为了应对这些挑战,我们首先应用Chang变换来解耦快速和慢速状态。接下来,我们使用状态转换将状态方程转换为块形式,以消除对完整行秩输入矩阵的要求。最后,利用反推法设计了规定的性能控制。通过两个实例:一个数值仿真和一个涉及电子电路系统的硬件在环实验,证明了所提出的控制策略的有效性和优越性。
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
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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