Stabilization for Networked Control Systems with Random Sampling Periods | Zendy

Yuan Li | Zendy; Qingling Zhang | Zendy; Shuanghong Zhang | Zendy; Min Cai | Zendy

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Stabilization for Networked Control Systems with Random Sampling Periods

Author(s) -

Yuan Li,

Qingling Zhang,

Shuanghong Zhang,

Min Cai

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/252679

Subject(s) - control theory (sociology) , inverted pendulum , controller (irrigation) , markov chain , sampling (signal processing) , linear matrix inequality , mathematics , stability (learning theory) , computer science , networked control system , full state feedback , discrete time and continuous time , mathematical optimization , control (management) , nonlinear system , statistics , physics , filter (signal processing) , quantum mechanics , artificial intelligence , machine learning , agronomy , computer vision , biology

This paper investigates the stabilization of networked control systems (NCSs) with random delays and random sampling periods. Sampling periods can randomly switch between three cases according to the high, low, and medium types of network load. The sensor-to-controller (S-C) random delays and random sampling periods are modeled as Markov chains. The transition probabilities of Markov chains do not need to be completely known. A state feedback controller is designed via the iterative linear matrix inequality (LMI) approach. It is shown that the designed controller is two-mode dependent and depends on not only the current S-C delay but also the most recent available sampling period at the controller node. The resulting closed-loop systems are special discrete-time jump linear systems with two modes. The sufficient conditions for the stochastic stability are established. An example of the cart and inverted pendulum is given to illustrate the effectiveness of the theoretical result

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