Abstract
This paper puts forward a method to design the H∞ filter for networked control systems (NCSs) with time delay and data packet loss. Based on the properties of Markovian jump system, the packet loss is treated as a constant probability independent and identically distributed Bernoulli random process. Thus, the stochastic stability condition can be acquired for the filtering error system, which meets an H∞ performance index level γ. It is shown that, by introducing a special structure of the relaxation matrix, a linear representation of the filter meeting an H∞ performance index level for NCSs with time delay and packet loss can be obtained, which uses linear matrix inequalities (LMIs). Finally, numerical simulation examples demonstrate the effectiveness of the proposed method.
Highlights
As a new generation of control systems, networked control systems (NCSs) [1,2,3,4,5,6,7,8,9,10] have attracted more and more researchers’ attention because of their extensive application
Compared with the traditional control system, NCSs have some advantages, such as easy wiring, installation, maintenance, expansion, reliability, and flexibility, so that resource sharing is achieved in such systems
The problem of NCSs with time delay and packet dropout phenomenon has become a hot topic in the control field [11,12,13]
Summary
As a new generation of control systems, NCSs [1,2,3,4,5,6,7,8,9,10] have attracted more and more researchers’ attention because of their extensive application. The problem of NCSs with time delay and packet dropout phenomenon has become a hot topic in the control field [11,12,13]. Many conclusions only consider time delay or packet loss separately, which is not very consistent with the actual situation of network application. The H∞ filter design of NCSs with time delay and packet dropout has not yet been considered widely. This paper studies the stability of networked control systems considering both time delay and packet loss. The analysis process is more complicated than considering time delay or packet loss alone, the conclusion is more general and universal, and the existence conditions of system filters are given. E{x} and Ex | y represent the expectation of event x and the expectation of x conditional on y, respectively
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