IF 7.5 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Expert Systems with Applications Pub Date : 2025-03-11 DOI:10.1016/j.eswa.2025.127092
Luyao You, Xiaodi Li
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引用次数: 0

摘要

本文针对涉及未知不匹配干扰的脉冲系统,研究了一种基于观测器的新型滑模控制问题。与现有的耦合已知干扰完整信息的滑模控制不同,我们提出的基于观测器的滑模控制依赖于干扰估计,并将干扰估计误差约束纳入开关增益设计。结果表明,所提出的基于观测器的滑动模态控制不仅隐含地抑制了未知不匹配干扰的负面影响,而且确保了在有限时间内达到所设计的滑动面。建立了一些脉冲系统的可达性标准,提出了不匹配干扰、脉冲作用和滑动功能之间的潜在关系。这种关系充分估计了离散动力学的影响,避免了由此产生的滑动模式动力学在脉冲瞬间跳出设计的滑动面。随后,基于一些线性矩阵不等式条件,得到了稳定所产生的滑动模式动力学的方法。最后,我们提供了两个实例来验证我们的结果,其中一个重点关注质量弹簧-阻尼器系统。
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Observer-based sliding mode control of impulsive systems with unknown mismatched disturbances
This paper studies a novel observer-based sliding mode control problem for impulsive systems involving unknown mismatched disturbances. Different from the existing sliding mode control coupling the complete information of known disturbances, our proposed observer-based sliding mode control depends on the disturbance estimation and incorporates the bound of disturbance estimation error into the switch gain design. It is shown that the proposed observer-based sliding mode control not only implicitly restrains the negative effects of unknown mismatched disturbances, but also ensures the reachability of the designed sliding surface in a finite time. Some reachability criteria of impulsive systems are established, where a potential relationship between mismatched disturbances, impulse actions, and sliding function is presented. This relationship fully estimates the effects of discrete dynamics and avoids the resulting sliding mode dynamics jumping out of the designed sliding surface at impulse instants. Following that, some linear matrix inequalities-based conditions are obtained to stabilize the resulting sliding mode dynamics. Finally, two examples are provided to verify our results, including the one focusing on the mass–spring-damper systems.
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来源期刊
Expert Systems with Applications
Expert Systems with Applications 工程技术-工程:电子与电气
CiteScore
13.80
自引率
10.60%
发文量
2045
审稿时长
8.7 months
期刊介绍: Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.
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