Name
Title | ||
|---|---|---|
Composite Trajectory Tracking Control of Unmanned Surface Vehicles with Disturbances and Uncertainties |
Abstract | ||
|---|---|---|
To attenuate the effect of uncertainties and unknown disturbances, a composite trajectory tracking control scheme using disturbance observer and neural networks (NN) is proposed for an unmanned surface vehicle (USV) in this paper. In the absence of uncertainties and unknown disturbances, by defining a nonsingular terminal sliding mode (NTSM) manifold, a NTSM-based controller is designed for the USV to guarantee the tracking errors exactly converge to zero within a finite time. In the presence of uncertainties and unknown disturbances, NN is employed to compensate uncertainties while a disturbance observer is applied to simultaneously observe NN approximation error and unknown disturbances. Simulation studies demonstrate the effectiveness of the proposed control scheme. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/RCAR.2018.8621836 | 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR) |
Keywords | Field | DocType |
unmanned surface vehicle,unknown disturbances,disturbance observer,NN,composite trajectory tracking control,neural networks,USV,NTSM,approximation error | Control theory,Unmanned surface vehicle,Control theory,Computer science,Observer (quantum physics),Artificial neural network,Approximation error,Trajectory,Manifold,Finite time | Conference |
ISBN | Citations | PageRank |
978-1-5386-6870-2 | 0 | 0.34 |
References | Authors | |
14 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ning Wang | 1 | 202 | 18.93 |
| Shaofan Guo | 2 | 0 | 0.68 |
| Jian-Chuan Yin | 3 | 76 | 12.14 |
| Zhongjiu Zheng | 4 | 12 | 1.51 |
| Hong Zhao | 5 | 105 | 16.53 |