Distributed Model-Free Adaptive Learning Control of Discrete-Time Nonlinear Multiagent Systems.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40498614.
- Also identified by DOI 10.1109/TNNLS.2025.3575423.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
This article investigates the distributed control problem for nonlinear multiagent systems (MASs) with unknown system models. A novel distributed model-free adaptive learning algorithm is developed to learn a controller from the online system data. Notably, a significant advancement over conventional methods is that the proposed algorithm requires only local interaction data from neighboring agents, eliminating dependencies on both a priori system structural knowledge and global topology information. Comprehensive simulations validate the theoretical results and demonstrate the superior efficacy of the devised algorithm.