Event-Triggered Cooperative Adaptive Optimal Output Regulation for Multiagent Systems Under Switching Network: An Adaptive Dynamic Programming Approach
针对未知多智能体系统在切换网络下的协同最优输出调节问题，提出一种事件触发自适应最优控制器，无需系统动力学模型，可降低计算通信成本，并通过协同自适应巡航控制应用验证。
This article investigates the event-triggered cooperative adaptive optimal output regulation problem for unknown multiagent systems (MASs) under switching network. To address communication disruptions between subsystems and the leader, a distributed observer is provided to estimate the reference signals. Without using system dynamics, an event-triggered mechanism is established to reduce computation and communication costs. Then, event-triggered adaptive optimal controllers are developed by using the available input/state data. By exploiting the Lyapunov stability theory and the method of input-to-state stability (ISS), rigorous stability analysis is conducted, and conditions for MASs to achieve the leader-to-formation stability (LFS) are provided. Additionally, the sensitivity of the suboptimality index to system parameters is analyzed. Finally, an application to cooperative adaptive cruise control (CACC) is presented to validate the proposed approach.