Analysis of Discrete-Time Switched Linear Systems Under Logical Dynamic Switching.

IF 10.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE transactions on neural networks and learning systems Pub Date : 2024-11-05 DOI:10.1109/TNNLS.2024.3487590
Xiao Zhang, Min Meng, Zhengping Ji
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Abstract

The control properties of discrete-time switched linear systems (SLSs) with switching signals generated by logical dynamical systems are studied using the semitensor product (STP) approach. With the algebraic state-space representation (ASSR), the linear modes and the logical generators are aggregated as a system with hybrid states, leading to the criteria of reachability, controllability, observability, and reconstructibility of the SLSs. Algorithms for checking these properties are given. Then, two kinds of realization problems concerning whether the logical dynamical systems can generate the desired switching signals are investigated, and necessary and sufficient conditions for the realizability of the desired switching signals are given with respect to the cases of fixed operating time (FOT) switching and finite reference signal switching.

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逻辑动态切换下的离散时间开关线性系统分析》(Analysis of Discrete-Time Switched Linear Systems Under Logical Dynamic Switching)。
本文采用半张量乘积(STP)方法研究了由逻辑动力系统产生开关信号的离散时间开关线性系统(SLS)的控制特性。通过代数状态空间表示(ASSR),线性模式和逻辑生成器被聚合为一个具有混合状态的系统,从而得出了 SLS 的可达性、可控性、可观测性和可重构性标准。本文给出了检查这些属性的算法。然后,研究了逻辑动力系统能否产生所需的开关信号的两种实现问题,并针对固定运行时间(FOT)开关和有限参考信号开关的情况,给出了所需开关信号可实现的必要条件和充分条件。
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来源期刊
IEEE transactions on neural networks and learning systems
IEEE transactions on neural networks and learning systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
CiteScore
23.80
自引率
9.60%
发文量
2102
审稿时长
3-8 weeks
期刊介绍: The focus of IEEE Transactions on Neural Networks and Learning Systems is to present scholarly articles discussing the theory, design, and applications of neural networks as well as other learning systems. The journal primarily highlights technical and scientific research in this domain.
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