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Stabilisation of networked control systems under a novel stochastic-sampling-based adaptive event-triggered scheme

机译：基于新型随机抽样的自适应事件触发方案下的网络控制系统稳定

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摘要

In order to save the usage of system resources and adapt the variation of plant state, this study first proposes a novel stochastic-sampling-based adaptive event-triggered scheme (AETS). Second, in the framework of time-delay systems, the closed-loop control system is modelled as a class of delayed stochastic systems where time-delay is distributed in some intervals with probability. Then, by employing stochastic analysis tool and Lyapunov stability theory, a stability criterion for this class of delayed stochastic systems is established to ensure that the system possesses stochastically asymptotic stability with an H-infinity disturbance attenuation performance. Also, a co-design of parameter matrices of the state-feedback controller and the stochastic-sampling-based AETS is implemented. Third, based on the obtained co-design condition, a convex optimisation algorithm for the tradeoffs between disturbance attenuation performance and resource utilisation of the closed-loop control system is further developed. Finally, the effectiveness and feasibility of the proposed control strategy are illustrated by two numerical examples of adaptive event-triggered control for networked control systems under stochastic sampling.
机译：为了节省系统资源的使用并适应植物状态的变化，本研究首先提出了一种新型随机采样的自适应事件触发方案（AET）。其次，在时间延迟系统的框架中，闭环控制系统被建模为一类延迟随机系统，其中时间延迟以具有概率的某些间隔分布。然后，通过采用随机分析工具和Lyapunov稳定性理论，建立了这种延迟随机系统的稳定性标准，以确保该系统具有随着H-Infinity扰动衰减性能的随机渐近稳定性。而且，实现了状态反馈控制器的参数矩阵和基于随机采样的AET的参数矩阵的共同设计。第三，基于所获得的共设计条件，进一步开发了一种用于闭环控制系统的扰动衰减性能与资源利用之间的折衷的凸优化算法。最后，通过随机采样下的网络控制系统的自适应事件触发控制的两个数值例子说明了所提出的控制策略的有效性和可行性。

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  • 来源
    《Control Theory & Applications, IET》 |2020年第9期|1158-1169|共12页
  • 作者

    Xie Xuhuan; Li Shanbin; Xu Bugong;

  • 作者单位

    South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China;

    South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China;

    South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China;

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