Name
Title | ||
|---|---|---|
Neural network based adaptive region tracking control for a swarm of ships in constrained space |
Abstract | ||
|---|---|---|
Region tracking controllers are investigated for a swarm of ships which have the limited sensing range. In this control method, all ships can synchronously the moving desired area while avoiding obstacles on the track. In order to keep the inter-connection of dynamic interaction systems, barrier potential function is included which can approach infinity when the argument approaches special limits. Decentralized controllers are designed via function approximation technique, backstepping recursive design methodology, potential functions, and Lyapunov stability analysis theory. Moreover, we introduced the dynamic and constrained target zone to make this problem much more applicable for various situations. The simulated examples are represented to demonstrate the validity of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICACI.2018.8377485 | 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI) |
Keywords | Field | DocType |
multi-agent systems,target zone following,obstacle avoidance,constrained space,neural networks,stability | Backstepping,Swarm behaviour,Function approximation,Control theory,Computer science,Infinity,Lyapunov stability,Design methods,Artificial neural network,Recursion | Conference |
ISBN | Citations | PageRank |
978-1-5386-4363-1 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoming Sun | 1 | 3 | 1.81 |
| Shuzhi Sam Ge | 2 | 170 | 10.19 |
| Qing Xu | 3 | 20 | 14.16 |