摘要
In this paper, we propose a robust model predictive control algorithm for discrete-time nonholonomic robot systems with additive disturbances. To achieve moving obstacle avoidance, the related polyhedral over-approximations are utilized to realize the reformulation of obstacle avoidance constraint. Thus, the resulting model predictive control optimization problem can be solved effectively by standard nonlinear programming solvers. Moreover, the theoretical guarantees for recursive feasibility and input-to-state stability are provided. Finally, the efficiency of the proposed algorithm is verified by the simulation results.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 2020 IEEE 16th International Conference on Control and Automation, ICCA 2020 |
| 出版商 | IEEE Computer Society |
| 页 | 1494-1499 |
| 页数 | 6 |
| ISBN（电子版） | 9781728190938 |
| DOI | |
| 出版状态 | 已出版 - 9 10月 2020 |
| 活动 | 16th IEEE International Conference on Control and Automation, ICCA 2020 - Virtual, Sapporo, Hokkaido, 日本 期限: 9 10月 2020 → 11 10月 2020 |
出版系列
| 姓名 | IEEE International Conference on Control and Automation, ICCA |
|---|---|
| 卷 | 2020-October |
| ISSN（印刷版） | 1948-3449 |
| ISSN（电子版） | 1948-3457 |
会议
| 会议 | 16th IEEE International Conference on Control and Automation, ICCA 2020 |
|---|---|
| 国家/地区 | 日本 |
| 市 | Virtual, Sapporo, Hokkaido |
| 时期 | 9/10/20 → 11/10/20 |
指纹
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Hao, Y., Dai, L., Xie, H., Guo, Y., & Xia, Y. (2020). Robust MPC for Nonholonomic Robots with Moving Obstacle Avoidance. 在 2020 IEEE 16th International Conference on Control and Automation, ICCA 2020 (页码 1494-1499). 文章 9264331 (IEEE International Conference on Control and Automation, ICCA; 卷 2020-October). IEEE Computer Society. https://doi.org/10.1109/ICCA51439.2020.9264331