Exponential convergence analysis of uncertain genetic regulatory networks with time-varying delays.
Exponential convergence analysis of uncertain genetic regulatory networks with time-varying delays.
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DOI：
10.1016/j.isatra.2014.05.017
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发表时间：
2014-09
期刊：
影响因子：
7.3
通讯作者：
Wenqin Wang;S. Nguang;S. Zhong;Feng Liu
中科院分区：
文献类型：
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作者：
Wenqin Wang;S. Nguang;S. Zhong;Feng Liu
本研究关注的是具有时变时滞的不确定遗传调控网络在平衡点未知的情况下的指数收敛问题。系统的不确定性被建模为结构化线性分数形式。通过使用下界引理和 Jensen 不等式引理获得了新的稳定性准则。为了摆脱时变延迟的导数必须小于1的严格约束，通过改进Lyapunov-Krasovskii泛函而不是使用传统的自由权矩阵，引入了一种新方法。最后，通过数值算例验证了理论结果的有效性。
This study is concerned with the problem of exponential convergence of uncertain genetic regulatory networks with time-varying delays in the case of the unknown equilibrium point. The system׳s uncertainties are modeled as a structured linear fractional form. Novel stability criteria are obtained by using the lower bound lemma together with Jensen inequality lemma. In order to get rid of the rigorous constraint that the derivatives of time-varying delays must be less than one, a new approach is introduced by improving Lyapunov–Krasovskii functional rather than using the traditional free-weighting matrices. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results.