Name
Title | ||
|---|---|---|
Data-based output tracking formation control for heterogeneous MIMO multiagent systems under switching topologies |
Abstract | ||
|---|---|---|
A data-based output tracking formation control strategy for nonlinear MIMO multiagent systems (MASs) is provided in this paper, where the dynamic of each agent is disparate. The novel linearization method is used to construct the agent models dynamically, and only one linearization parameter needs to be estimated via I/O data. Then, the data-driven formation control protocol is presented for heterogeneous MIMO MASs under switching topologies. The convergence analysis using contraction mapping principle shows that the output tracking errors of the group of agents are uniformly ultimately bounded. We also prove that the presented formation control protocol can be extended to the MASs with time-variable geometry formation. The combination of data-driven method, heterogeneous MASs, MIMO agent, switching topologies and time-varying formation control makes the presented control strategy more general and practical. In the end, two simulation experiments are given to elucidate the effectiveness of this formation control protocol of MASs. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.neucom.2020.10.017 | Neurocomputing |
Keywords | DocType | Volume |
Heterogeneous multiagent systems,Data-based,Model free adaptive control,Time-varying formation control,Output tracking,Switching topologies | Journal | 422 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weizhao Song | 1 | 1 | 1.70 |
| Jian Feng | 2 | 3 | 1.49 |
| Shaoxin Sun | 3 | 0 | 0.34 |