Name
Title | ||
|---|---|---|
An Asymptotically Stable Identifier Design For Unmanned Surface Vehicles Based On Neural Networks And Robust Integral Sign Of The Error |
Abstract | ||
|---|---|---|
In this paper, a robust identifier is developed for unmanned surface vehicles (USVs) subject to uncertain dynamics. The uncertain dynamics comes from parametric model uncertainty and external ocean disturbance. The identifier for USV is designed based on Robust Integral Sign of the Error (RISE) and neural networks. With the proposed identifier, asymptotic stability of the estimation errors can be proven in the presence of parametric model uncertainties and external ocean disturbances. The proposed method can be used in a variety of practical settings such as trajectory tracking and formation control of marine vehicles for achieving better performance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-22808-8_6 | ADVANCES IN NEURAL NETWORKS - ISNN 2019, PT II |
Keywords | Field | DocType |
Neural networks, Unmanned surface vehicle, Derivative estimation, Robust identification | Parametric model,Unmanned surface vehicle,Identifier,Pattern recognition,Computer science,Control theory,Exponential stability,Artificial intelligence,Derivative estimation,Artificial neural network,Trajectory,Stability theory | Conference |
Volume | ISSN | Citations |
11555 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengnan Gao | 1 | 0 | 0.68 |
| Lu Liu | 2 | 1501 | 170.70 |
| Zhouhua Peng | 3 | 645 | 36.02 |
| Dan Wang | 4 | 714 | 38.64 |
| Nan Gu | 5 | 9 | 2.13 |
| Yue Jiang | 6 | 0 | 0.68 |