Sampling rate tracking control of networked control systems based on cognitive knowledge of packet disordering

Jinna Li, Lifeng Wei, Daqing Zhang, Chao Liu, Haibin Yu, Qingling Zhang
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Abstract

This paper focuses on the sampling rate tracking control of networked control systems (NCSs) with packet disordering. In view of the coupled relation between packet disordering and sampling rate, a novel sampling rate control algorithm, referring to the cognitive knowledge of packet disordering, is presented. Based on it, a controller that jointly controls sampling rate and the plant is proposed, and an augmented model of NCSs is constructed. A sufficient condition under which the close-loop systems are stochastically stable is derived. Moreover, the actual sampling period tracks a desired sampling period according to tracking control method. The controller design is presented for NCSs in terms of linear matrix inequalities (LMIs) technique. Finally, A numerical example is given to illustrate the effectiveness of the proposed method.
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基于数据包无序认知知识的网络控制系统采样率跟踪控制
研究了具有分组无序的网络控制系统的采样率跟踪控制问题。针对分组无序与采样率之间的耦合关系,提出了一种基于分组无序认知知识的采样率控制算法。在此基础上,提出了一种联合控制采样率和被控对象的控制器,并构造了ncs的增广模型。给出了闭环系统随机稳定的充分条件。此外,实际采样周期根据跟踪控制方法跟踪期望采样周期。根据线性矩阵不等式(lmi)技术,提出了ncs的控制器设计。最后,通过一个算例说明了所提方法的有效性。
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