输入饱和不确定双时间尺度系统的鲁棒半全局输出调节

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Yan Lei, Yan-Wu Wang, Irinel-Constantin Morărescu, Daniele Astolfi
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引用次数: 0

摘要

研究了具有输入饱和的不确定线性系统的鲁棒半全局输出调节问题。在这种设置中,不能应用现成的技术来拒绝由于两个时间尺度引起的数值问题以及由于输入饱和产生的技术问题而导致的结构不确定性。为了解决这一问题,我们将内模原理与低增益技术和奇异摄动理论相结合。显然,调节器的设计是基于Sylvester方程的解的计算,该方程在双时间尺度下可能是病态的。为了克服这个问题,我们提出了一个易解方程,并在一些标准假设下保证了其解的存在唯一性。在此基础上,设计了一种基于内模的控制器,解决了半全局鲁棒输出调节问题。为了应对输入饱和,我们将系外系统状态无穷范数的极限上界限定并满足一定的约束条件。最后,通过三个算例说明了所得结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Semi-Global Output Regulation of Uncertain Two-Time-Scale Systems With Input Saturation

This paper investigates the robust semi-global output regulation of uncertain linear systems with input saturation. In this setup, one cannot apply off-the-shelf techniques to reject structural uncertainties due to numerical issues caused by the two time scales but also due to technical issues generated by the input saturation. To solve this problem, we combine internal model principle with low gain technique and singular perturbation theory. Explicitly, the regulator design is based on the computation of the solutions of a Sylvester equation, which can be ill-conditioned in the two-time scales setting. To overcome this, we propose an easily solvable equation, and the existence and uniqueness of its solution are guaranteed under some standard assumptions. Accordingly, an internal model-based controller is designed such that the semi-global robust output regulation problem can be solved. In order to cope with the input saturation, we impose that the ultimate upper bound of the infinity norm of the exosystem state is limited and satisfies certain constraints. Finally, three examples are provided to illustrate the effectiveness of the results.

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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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