Name
Title | ||
|---|---|---|
Coordination control of uncertain topological high-order multi-agent systems: distributed fuzzy adaptive iterative learning approach |
Abstract | ||
|---|---|---|
This paper demonstrates that the method of T–S fuzzy model can be used to describe the uncertain topological structure for high-order linearly parameterized multi-agent systems (MAS). The dynamic of the leader is only available to a portion of the follower agents; thus, we present a novel distributed adaptive iterative learning control (AILC) protocol without using any global information to deal with the consensus problem of MAS under initial-state learning condition. It is proved that the proposed control protocol ensures all the internal signals in the multi-agent system are bounded, and the follower agents track the leader exactly on the finite time interval [0, T]; a sufficient condition is obtained for the exactly consensus result of the multi-agent system by choosing the appropriate composite energy function. Extensions to the formation control of multi-agent systems are also given. In the end, illustrative examples are shown to verify the availability of the proposed AILC scheme. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s00500-018-3271-1 | soft computing |
Keywords | Field | DocType |
Multi-agent system, Coordination, AILC, T–S fuzzy models, Uncertain topological structure, Initial-state learning condition | Consensus,Topology,Mathematical optimization,Parameterized complexity,Computer science,Global information,Fuzzy logic,Multi-agent system,Iterative learning control,Bounded function,Finite time | Journal |
Volume | Issue | ISSN |
23.0 | 15.0 | 1433-7479 |
Citations | PageRank | References |
2 | 0.36 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Wu | 1 | 8 | 3.52 |
| Jun-Min LI | 2 | 390 | 36.09 |