Nonlinear Cooperative Output Regulation With Input Delay Compensation

• 成果类型: Article
• 署名作者: Zheng, Shiqi; Ahn, Choon Ki; Jiang, Xiaowei; Yan, Huaicheng; Shi, Peng
• 署名单位: China University of Geosciences; Korea University; East China University of Science & Technology; University of Adelaide
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3462634
• 发表日期: 2025
• 页码: 1336-1343
• 关键词: Delays; observers; Nonlinear systems; regulation; Robot sensing systems; Multi-agent systems; monitoring; event-triggered control; input delay; mutliagent systems (MASs); ordinary differential equations-partial differential equations (ODE-PDE)

摘要

This article investigates the cooperative output regulation (COR) of nonlinear multiagent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event-triggered control can automatically guarantee a Zeno-free behavior and avoid the continuous monitoring of triggered conditions. First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information. Second, a new distributed predictor feedback control method is proposed for the considered nonlinear MASs with input delay. By coordinate transformation, the MASs are mapped into new coupled ordinary differential equations-partial differential equations (ODE-PDE) target systems with some disturbance-like terms. Then, we show that the COR problem is solvable. At last, to further save the communication resource, a periodic event-triggered mechanism is considered in the sensor-to-controller transmission in every agent. A new periodic event-triggered filter is proposed to deal with the periodic event-triggered feedback data. The MASs with input delay are mapped into coupled ODE-PDE target systems with sampled data information. Then, Lyapunov-Krasovskii functions are constructed to demonstrate the exponential stability of the MASs. Simulations verify the validity of the proposed results.