Interval type-2 fuzzy control for nonlinear system via adaptive memory-event-triggered mechanism

This article focuses on the issue of adaptive memory-event-triggered control for a class of interval type-2 Takagi-Sugeno fuzzy system (IT-2 TSFS) subjected to network-induced delays. Firstly, the IT-2 TSFS is established to effectively describe the non-linearities and parameter uncertainties. Secondly, in order to decrease the burden of network transmission, a novel adaptive memory-event-triggered mechanism (AMETM) is presented by employing a buffer in event-triggered module. The historical information stored in the buffer is used to select the necessary control signal. Furthermore, the proposed AMETM can adaptively adjust the threshold to balance the data releasing rate and control performance. Then, the stability analysis is carried out by utilizing the discontinuous looped Lyapunov-Krasovskii functional. The properties of fuzzy membership functions are used to derive the improved stability conditions, which ensure the H infinity performance. Finally, the numerical example is represented to verify the advantages of the control method.

Automated summary

This article focuses on adaptive memory-event-triggered control for a class of interval type-2 Takagi-Sugeno fuzzy system subjected to network-induced delays. It proposes a novel adaptive memory-event-triggered mechanism by employing a buffer in the event-triggered module to decrease the burden of network transmission. The proposed mechanism can adaptively adjust the threshold to balance the data releasing rate and control performance. The improved stability conditions are derived using fuzzy membership functions to ensure H infinity performance.