Name
Abstract | ||
|---|---|---|
This paper focuses on horizontal path following for an underactuated unmanned airship under output constraints and uncertainties. To handle the output constraints, we design a guidance loop based on a novel time-varying tan-type barrier Lyapunov function to generate the desired yaw angle. By using the backstepping technique, the controller is then designed to realize the desired yaw and velocity tracking. For uncertainties and disturbances, an adaptive radial basis function neural network is applied for estimation and compensation. Moreover, to avoid complex derivative calculations for virtual control and guarantee that the desired attitude is bounded, a command filter and an auxiliary system are combined in the system. Theoretical analysis shows that, despite the influence of disturbances, the designed controller ensures that the constraint of airship position is never violated while the closed loop signals are all uniformly ultimately bounded. Comparable simulations illustrate the performance of our controller. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.engappai.2019.06.021 | Engineering Applications of Artificial Intelligence |
Keywords | Field | DocType |
Unmanned airship,Path-following control,Output constraint,Backstepping,Neural network | Control theory,Backstepping,Mathematical optimization,Virtual control,Computer science,Control theory,Radial basis function neural,Path following,Euler angles,Underactuation,Bounded function | Journal |
Volume | ISSN | Citations |
85 | 0952-1976 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zewei Zheng | 1 | 4 | 2.09 |
| Zhiyuan Guan | 2 | 0 | 0.68 |
| Yunpeng Ma | 3 | 0 | 0.34 |
| Bing Zhu | 4 | 99 | 14.45 |