Name
Title | ||
|---|---|---|
Q-Learning-based parameters adaptive algorithm for active disturbance rejection control and its application to ship course control |
Abstract | ||
|---|---|---|
•First, we design a LADRC ship course controller to deal with nonlinearity and uncertainty caused by complex sea conditions, such as wind, waves and load.•Second, to achieve better control performance, we propose an adaptive algorithm based on Q-learning.•Furthermore, some desired states are initialized with higher probability during the training in order to train the corresponding Q-value more adequately. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2019.10.060 | Neurocomputing |
Keywords | DocType | Volume |
Q-Learning,Reinforcement learning,Adaptive control,Active disturbance rejection control (ADRC),Ship course control | Journal | 408 |
ISSN | Citations | PageRank |
0925-2312 | 1 | 0.38 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zeng-Qiang Chen | 1 | 550 | 72.38 |
| Beibei Qin | 2 | 1 | 0.38 |
| Mingwei Sun | 3 | 2 | 4.79 |
| Qinglin Sun | 4 | 1 | 1.06 |