Non-fragile sampled-data robust synchronization of uncertain delayed chaotic Lurie systems with randomly occurring controller gain fluctuation.
Non-fragile sampled-data robust synchronization of uncertain delayed chaotic Lurie systems with randomly occurring controller gain fluctuation.
复制标题
DOI：
10.1016/j.isatra.2016.11.002
复制
发表时间：
2017
期刊：
影响因子：
7.3
通讯作者：
Kaibo Shi;Yuanyan Tang;Xinzhi Liu;S. Zhong
中科院分区：
文献类型：
--
作者：
Kaibo Shi;Yuanyan Tang;Xinzhi Liu;S. Zhong
提出了一种新的非脆弱随机控制方法来研究变时滞不确定混沌Lurie系统的鲁棒采样数据同步问题。假设控制器增益波动和时变的不确定参数是随机的，且满足一定的Bernoulli分布白噪声序列。此外，通过选择适当的Lyapunov-Krasovskii泛函(LKF)，充分利用了关于实际采样模式和非线性条件的信息，提出了一种新的同步判据，用于分析相应的同步误差系统。此外，基于最强大的基于自由矩阵的积分不等式(FMBII)，借助于线性矩阵不等式的解，得到了期望的非脆弱采样数据估计器控制器。最后，给出了蔡氏电路和神经网络的三个数值仿真实例，验证了所提理论结果的有效性和优越性。
This paper proposes a new non-fragile stochastic control method to investigate the robust sampled-data synchronization problem for uncertain chaotic Lurie systems (CLSs) with time-varying delays. The controller gain fluctuation and time-varying uncertain parameters are supposed to be random and satisfy certain Bernoulli distributed white noise sequences. Moreover, by choosing an appropriate Lyapunov-Krasovskii functional (LKF), which takes full advantage of the available information about the actual sampling pattern and the nonlinear condition, a novel synchronization criterion is developed for analyzing the corresponding synchronization error system. Furthermore, based on the most powerful free-matrix-based integral inequality (FMBII), the desired non-fragile sampled-data estimator controller is obtained in terms of the solution of linear matrix inequalities. Finally, three numerical simulation examples of Chua's circuit and neural network are provided to show the effectiveness and superiorities of the proposed theoretical results.