Event-Triggered Real-Time Scheduling Fuzzy Stabilization based on A Variable-Weights Method

This paper mainly uses a variable-weights method to deal with the event-triggered real-time scheduling fuzzy stability problem. With the continuous research of the variable-weights method, the hidden information of nonlinear plants is discovered and fully utilized. In each sample point of the schedule process, the event-triggered real-time scheduler can make a decision which control mode will be used by considering the joint-distribution of periodic and differential past and present normalized fuzzy weighting functions activation. In fact, as long as the current joint distribution has changed, the corresponding activated control modes must be updated with their respective matrices to meet different time-varying conditions, and the existing system stability can also be significantly improved. A simulation example is used to verify the virtue of the method in the end.