Quantized $H_{\infty }$ Control for Nonlinear Stochastic Time-Delay Systems With Missing Measurements

Quantized $H_{\infty }$ Control for Nonlinear Stochastic Time-Delay Systems With Missing Measurements
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DOI:
10.1109/tac.2011.2176362
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发表时间:
2012-06
影响因子:
6.8
通讯作者:
Zidong Wang;Bo Shen;H. Shu;G. Wei
Zidong Wang;Bo Shen;H. Shu;G. Wei
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zidong Wang;Bo Shen;H. Shu;G. Wei

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研究了一类具有概率数据缺失的非线性随机时滞网络系统的量化H∞控制问题。采用一个具有状态时滞的非线性随机系统对网络控制系统进行建模,其中测量输出和输入信号分别由两个对数量化器量化。此外,通过引入由取值为1和0的伯努利分布随机变量组成的对角矩阵,描述了来自不同传感器的数据可能以不同的丢失概率丢失,对数据丢失现象进行了建模。然后,利用扇区有界不确定性方法,给出了在零初始条件下,对于所有非零外扰,闭环系统随机稳定且控制输出满足H∞性能约束的充分条件。然后将充分条件分解为若干不等式,以便于实际验证。在此基础上,利用Matlab线性矩阵不等式工具箱,成功地设计了几类特殊的非线性随机时滞系统的量化H∞控制器。最后,数值仿真算例表明了所得结果的有效性和适用性。
In this paper, the quantized H∞ control problem is investigated for a class of nonlinear stochastic time-delay network-based systems with probabilistic data missing. A nonlinear stochastic system with state delays is employed to model the networked control systems where the measured output and the input signals are quantized by two logarithmic quantizers, respectively. Moreover, the data missing phenomena are modeled by introducing a diagonal matrix composed of Bernoulli distributed stochastic variables taking values of 1 and 0, which describes that the data from different sensors may be lost with different missing probabilities. Subsequently, a sufficient condition is first derived in virtue of the method of sector-bounded uncertainties, which guarantees that the closed-loop system is stochastically stable and the controlled output satisfies H∞ performance constraint for all nonzero exogenous disturbances under the zero-initial condition. Then, the sufficient condition is decoupled into some inequalities for the convenience of practical verification. Based on that, quantized H∞ controllers are designed successfully for some special classes of nonlinear stochastic time-delay systems by using Matlab linear matrix inequality toolbox. Finally, a numerical simulation example is exploited to show the effectiveness and applicability of the results derived.