In this article, a decentralized event‐triggered control (ETC) strategy is developed for nonlinear large‐scale systems subjects to matched interconnections. First, the large‐scale interconnected systems are transformed to several nominal isolated subsystems. Then, the optimal control problem of nominal isolated subsystems is solved via an event‐triggered method based on adaptive critic learning. Note that the ETC scheme is adopted to reduce the computational burden and communication resources. Moreover, a single network adaptive critic structure is constructed to approximate the optimal cost and the control policy. By employing a stabilizing term in the weight updating law of the critic neural network, there is no requirement for adopting initial admissible control in the proposed algorithm. Furthermore, we use the Lyapunov method to demonstrate that estimated weight vectors used in the critic networks are uniformly ultimately bounded. Finally, we provide an example to validate the proposed decentralized event‐triggered control strategy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.