具有双输入时滞的网络控制系统稳定性的改进结果
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摘要
本文研究具有双输入时滞的网络控制系统的稳定性.本文首先把整个时滞区间划分为三个子区间并构造了一个新的Lyapunov泛函,该泛函可以充分利用所有时滞的信息.然后本文运用Wirtinger不等式得到了网络控制系统全局渐近稳定的充分判据.仿真算例验证了结果的有效性.同已有结果相比,本文的结果的保守性更低.
Stability analysis for a networked control system with two additive input delays is considered.By spitting the whole delay interval into three subintervals,a new Lyapunov-Krasovskii functional is constructed,which can make full use of the information of all the delays.Then,based on the constructed Lyapunov-Krasovskii functional and using Wirtinger-based inequality,sufficient conditions are derived to ensure the global asymptotic stability of the networked control system.Finally,a numerical example is provided to show the effectiveness of the criterion.In comparison with the known results,the obtained stability criterion is less conservative.
Stability analysis for a networked control system with two additive input delays is considered.By spitting the whole delay interval into three subintervals,a new Lyapunov-Krasovskii functional is constructed,which can make full use of the information of all the delays.Then,based on the constructed Lyapunov-Krasovskii functional and using Wirtinger-based inequality,sufficient conditions are derived to ensure the global asymptotic stability of the networked control system.Finally,a numerical example is provided to show the effectiveness of the criterion.In comparison with the known results,the obtained stability criterion is less conservative.
引文
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[2]Zhang X M,Han Q L.Event-triggered dynamic output feedback control for networked control systems[J].IET Control Theory A,2014,8:226.
[3]Zeng D,Zhang R,Zhong S,et al.Novel Lebesgue-integral-based approach to improved results for neural networks with additive time-varying delay components[J].J Franklin I,2017,354:7543.
[4]周伟松,赵永红.带时变时延效应的模糊神经网络均方指数输入的状态稳定性[J].四川大学学报:自然科学版,2016,53:731.
[5]Zhang R,Zeng D,Zhong S.Novel master-slave synchronization criteria of chaotic Lur’e systems with time delays using sampled-data control[J].J Franklin I,2017,354:4930.
[6]Zhang R,Zeng D,Zhong S,et al.Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays[J].Appl Math Comput,2017,310:57.
[7]冀娜,李洪旭.时滞对数种群竞争模型概周期解的存在性和全局稳定性[J].四川大学学报:自然科学版,2015,52:1187.
[8]Lee T H,Park J H.Improved criteria for sampleddata synchronization of chaotic Lur’e systems using two new approaches[J].Nonlinear Anal-Hybri,2017,24:132.
[9]Shi K,Liu X,Zhu H,et al.Novel integral inequality approach on master-slave synchronization of chaotic delayed Lur’e systems with sampled-data feedback control[J].Nonlinear Dynam,2016,83:1259.
[10]Rakkiyappan R,Chandrasekar A,Cao J.Passivity and passification of memristor-based recurrent neural networks with additive time-varying delays[J].IEEE T Neur Net Lear,2015,26:2043.
[11]Lam J,Gao H,Wang C.Stability analysis for continuous systems with two additive time-varying delay component[J].Syst Control Lett,2007,56:16.
[12]Gao H,Chen T,Lam J.A new delay system approach to network-based control[J].Automatica,2008,44:39.
[13]Yu X,Wang X,Zhong S,et al.Further results on delay-dependent stability for continuous system with two additive time-varying delay components[J].ISA T,2016,265:748.
[14]Li P.Further results on delay-range-dependent stability with additive time-varying delay systems[J].ISA T,2014,53:258.
[15]Ge X.Comments and an improved result on“stability analysis for continuous system with additive time-varying delays:a less conservative result”[J].Appl Math Comput,2014,241:42.
[16]Hui J,Kong X.Delay-partitioning approach for systems with interval time-varying delay and nonlinear perturbations[J].Appl Math Ser B,2015,281:74.
[17]Ji M,He Y.Further results on exponential stability of neural networks with time-varying delay[J].Appl Math Ser B,2015,256:175.
[18]Rakkiyappan R,Chandrasekar A,Cao J.Passivity and passification of memristor-based recurrent neural networks with additive time-varying delays[J].IEEE T Neur Net Lear,2015,26:2043.