Name
Title | ||
|---|---|---|
Leader-Follower Formation Control Using Cerebellar Perceptron Improved Model with Auto-structuring |
Abstract | ||
|---|---|---|
This paper proposes an intelligent formation control method of the leader and follower agents with nonlinear dynamics using our proposed cerebellar perceptron improved model with auto-structuring mechanism. In the proposed method, each agent can follow the leader, exchanging only information of positions (without velocities) of the observable agents including the leader and taking a predefined formation. In the real world, the method that doesn't need a lot of information to make cooperative behaviors is very useful for such cases of environments existing weak communications. In the computer simulation, it is verified that the proposed method is useful in the points of performance of the leader-following formation control without velocity and of the changeable environment. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CSE-EUC-DCABES.2016.218 | 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES) |
Keywords | Field | DocType |
mult agent,formation control,cerebellar perceptron improved model,autostructuring | Nonlinear system,Leader follower,Computer science,Robustness (computer science),Artificial intelligence,Control system,Fuzzy control system,Structuring,Artificial neural network,Perceptron | Conference |
ISBN | Citations | PageRank |
978-1-5090-3594-6 | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masanao Obayashi | 1 | 198 | 26.10 |
| Takeshi Aridome | 2 | 0 | 0.34 |
| Takashi Kuremoto | 3 | 196 | 27.73 |
| Shingo Mabu | 4 | 493 | 77.00 |