Name
Title | ||
|---|---|---|
Sequential adaptive switching time optimization technique for optimal control problems |
Abstract | ||
|---|---|---|
The control parameterization method used together with time-scaling transformation is an effective approach to transform optimal control problems into optimal parameter selection problems. The approximate problems can then be solved by gradient-based optimization methods. However, the conventional time-scaling transformation requires that all the control component functions switch simultaneously, which can be undesirable in practice. In this paper, we introduce a novel technique where the switching times for each of the control component functions can be adaptively selected. To demonstrate the effectiveness and flexibility of the proposed approach, two example problems with control input and terminal state constraints are solved using the method proposed. Numerical results show that the new method achieves much better objective values with some increase in computation time compared to the conventional time-scaling transformation technique. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.automatica.2022.110565 | Automatica |
Keywords | DocType | Volume |
Optimal control,Control parameterization,Switching time optimization,Time-scaling transformation,Gradient-based optimization | Journal | 146 |
Issue | ISSN | Citations |
1 | 0005-1098 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xi Zhu | 1 | 0 | 0.34 |
| Changjun Yu | 2 | 78 | 8.67 |
| K. L. Teo | 3 | 1643 | 211.47 |