To Transmit or Not to Transmit: A Discrete Event-Triggered Communication Scheme for Networked Takagi–Sugeno Fuzzy Systems

TLDR

The paper proposes a discrete event‑triggered communication scheme for networked Takagi‑Sugeno fuzzy systems. The scheme decides transmission based on the current sampled state and its error with the last transmitted state, employs a networked T‑S fuzzy model that accounts for nonuniform time scales and distributed compensation rules, and derives stability and stabilization criteria to balance communication resources and performance. Compared to periodic and continuous event‑triggered schemes, the proposed method significantly reduces bandwidth usage, eliminates the need for continuous measurement hardware, and offers a stability criterion that trades communication resources for performance, as demonstrated in a numerical example.

Abstract

This paper first proposes a discrete event-triggered communication scheme for a class of networked Takagi-Sugeno (T-S) fuzzy systems. This scheme has two main features: 1) Whether or not the sampled state should be transmitted is determined by the current-sampled state and the error between the current-sampled state and the latest transmitted state. Compared with those in a periodic time-triggered communication scheme, the communication bandwidth utilization is considerably reduced while preserving the desired control performance; and 2) it is a discrete event-triggered communication scheme due to the fact that the triggered conditions are only measured and checked at a constant sampling period. Compared with a continuous event-triggered communication scheme, the special hardware for continuous measurement and computation is no longer needed. Second, a networked T-S fuzzy model is delicately constructed, which not only considers nonuniform time scales in the networked T-S fuzzy model and the parallel distributed compensation fuzzy control rules but includes the aforementioned state error as well. Third, a stability criterion and a stabilization criterion about the networked T-S fuzzy system are derived, respectively. The stability criterion and stabilization criterion can provide a tradeoff to balance the required communication resource and the desired performance: Lowering the desired performance allows the network to allocate more limited bandwidth to other nodes in need. Finally, a numerical example is given to show the effectiveness of the proposed method.