Observer-based event-triggered optimal control for unknown nonlinear stochastic multi-agent systems with input constraints
Chen Liu, Lei Liu, Zhaojing Wu, Jinde Cao, Jianlong Qiu · Research Square · 2022
Abstract This paper addresses the observer-based event-triggered optimal control (ETOC) for nonlinear Itô-type stochastic multi-agent systems (SMASs) with unknown internal states and input constraints. To begin with, the event-triggered stochastic Hamilton-Jacobi-Bellman (HJB) equation with input constraints is presented for the first time. Next, the observer-based identifier network is utilized to recover the knowledge of unknown system dynamics. After that, the approximate event-triggered optimal controller is designed via adaptive critic designs (ACDs) whose weights are only updated at the triggering instants. It is worth mentioning that there is no published literature on the ETOC for nonlinear SMASs with unknown internal states and input constraints via the framework of ET-ACDs. This study is the first attempt to solve this problem. Moreover, it is also proved that the Zeno behavior does not exist in the closed-loop system. Finally, we present two examples to further verify the validity of the ETOC scheme.