Abstract
This paper investigates the dynamic event-triggered predictive control problem of interval type-2 (IT2) fuzzy systems with imperfect premise matching. First, an IT2 fuzzy systems model is proposed, including a dynamic event-triggered mechanism, which can save limited network resources by reducing the number of data packets transmitted, and a predictive controller, which can predict the state of the system between the two successful transmitted instants to deal with unreliable communication networks. Then, according to the Lyapunov stability theory and imperfect premise matching method, sufficient conditions for system stabilization and the controller gain are obtained. Finally, the validity of the proposed method is demonstrated by the numerical examples.
Highlights
Event-Triggered Predictive ControlNetworked control systems (NCSs) have attracted more attention during the past decades [1,2,3,4,5,6] due to their wide engineering applications, are control systems that connect various physical devices through a communication network with limited bandwidth in reality
An interval type-2 (IT2) T-S fuzzy model is used for modeling a class of NCSs, and an fuzzy eventtriggered predictive controller (FETPC) design method for systems considered with imperfect premise matching is proposed
The designed FETPC can predict the state of the system between two successful transmissions
Summary
Event-Triggered Predictive ControlNetworked control systems (NCSs) have attracted more attention during the past decades [1,2,3,4,5,6] due to their wide engineering applications, are control systems that connect various physical devices through a communication network with limited bandwidth in reality. It is desirable to have triggering laws whose threshold parameters are adaptively tuned depending on dynamical changes with the purpose of further reducing frequencies of signal transmissions. Following this line, a dynamic or adaptive. Some dynamic ETM might have a singular problem and degrade into a traditional time-triggered mechanism, which may restrict its use in practical applications. The multiplicative and additive internal dynamic variables of ETM are designed to avoid singular phenomena [17,18]. ETM may cause some practical problems due to the event triggered interval being too large for practical applications. We set the maximum eventtriggered interval to avoid these problems
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