Affiliation:
1. School of Artificial Intelligence, Tiangong University, Tianjin, China
2. School of Control Science and Engineering, Tiangong University, Tianjin, China
Abstract
In this article, the event-based predictive control problem for a class of interval type-2 Takagi–Sugeno fuzzy system is investigated. To reduce the influence of Gaussian noise, an improved Kalman filter is proposed, in which the system state is filtered or not depends on an event-triggered mechanism. Then, by designing the network predictive control scheme via interval type-2 fuzzy model, some sufficient conditions are derived, which guarantee the Schur stabilization of the concerned system subject to network delays. Finally, the correctness and effectiveness are verified by two simulation examples.
Funder
National Natural Science Foundation of China