Data-Driven Polytopic Output Synchronization From Noisy Data

• 成果类型: Article
• 署名作者: Li, Yifei; Liu, Wenjie; Wang, Gang; Sun, Jian; Xie, Lihua; Chen, Jie
• 署名单位: Beijing Institute of Technology; Nanyang Technological University; Tongji University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3411832
• 发表日期: 2024
• 页码: 8513-8525
• 关键词: Synchronization; noise; Noise measurement; mathematical models; regulators; Protocols; Symmetric matrices; Data-driven control; heterogeneous multiagent system (MAS); noisy data; output synchronization; polytope

摘要

This article proposes a novel approach to address the output synchronization problem for unknown heterogeneous multiagent systems (MASs) using noisy data. Unlike existing studies that focus on noiseless data, we introduce a distributed data-driven controller that enables all heterogeneous followers to synchronize with a leader's output trajectory. To handle the noise in the state-input-output data, we develop a data-based polytopic representation for the MAS. We tackle the issue of infeasibility in the set of output regulator equations caused by the noise by seeking approximate solutions via constrained fitting error minimization. This method utilizes measured data and a noise-matrix polytope to ensure near-optimal output synchronization, in the sense of ultimately uniformly boundedness stability. Stability conditions in the form of data-dependent semidefinite programs are derived, providing stabilizing controller gains for each follower. The proposed distributed data-driven control protocol achieves near-optimal output synchronization by ensuring the convergence of the tracking error to a bounded polytope, with the polytope size positively correlated with the noise bound. Numerical tests validate the practical merits of the proposed data-driven design and theory.