Asynchronous Stabilization of Boolean Control Networks With Stochastic Switched Signals

Mei Fang, Liqing Wang, Zhengguang Wu
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引用次数: 43

Abstract

This paper includes some results of switched Boolean control networks. The switched signals considered in this paper is time variant and it follows a certain probabilistic distribution vector. Given a concept of stabilization with stochastic switched signals, we obtained a necessary and sufficient condition for stabilization. Then a state feedback control depending on switched signals is designed to stabilize the system considered. Later we investigate a case when the switched signal $\theta (t)$ is unknown at time $t$ , and what we have is the prediction switched signal $\hat {\theta }(t)$ . For a given prediction matrix, a necessary and sufficient condition is given to preserve the stabilization. Except state feedback control, asynchronous pinning control for switched Boolean networks (BNs) is also considered. A necessary and sufficient condition is extended for the stability of BNs with stochastic switched signals. Moreover, algorithms are presented to find the minimal number of pinned nodes based on controlling minimal number of subsystems. Examples are shown to illustrate the effectiveness of the obtained results.
随机开关信号布尔控制网络的异步镇定
本文给出了开关布尔控制网络的一些研究结果。本文所考虑的开关信号是时变的,它遵循一定的概率分布向量。给出了随机开关信号镇定的概念,得到了镇定的充分必要条件。然后设计了一种依赖于开关信号的状态反馈控制来稳定所考虑的系统。后来我们研究了一个切换信号$\theta (t)$在时间$t$未知的情况,我们得到的是预测切换信号$\hat {\theta }(t)$。对于给定的预测矩阵,给出了保持其稳定性的充分必要条件。除状态反馈控制外,还考虑了交换布尔网络的异步固定控制。推广了随机开关信号bn稳定性的一个充分必要条件。提出了在控制最小子系统数量的基础上求最小固定节点数的算法。通过算例说明所得结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
0.00%
发文量
1
审稿时长
6.0 months
期刊介绍: The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the fields of systems engineering. It includes issue formulation, analysis and modeling, decision making, and issue interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems. In addition, it includes systems management, systems engineering processes, and a variety of systems engineering methods such as optimization, modeling and simulation.
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