Adaptive critic optimization to decentralized event‐triggered control of continuous‐time nonlinear interconnected systems
Yu Huo, Ding Wang, Junfei Qiao
Abstract
Abstract 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.