Multi-agent Distributed Formation Control Based on Improved Artificial Potential Field and Neural Network for Connectivity Preservation
文献类型：会议论文
| 作者 | Chen, Bao1; Ma HJ(马宏军)1; Kang HB(康浩博)3 ; Liang, Xinkai2
|
| 出版日期 | 2021 |
| 会议日期 | October 15-17, 2021 |
| 会议地点 | Beijing, China |
| 关键词 | Multi-AUV system formation control connectivity preservation artificial potential function |
| 页码 | 455-460 |
| 英文摘要 | In this brief, the collision avoidance and connectivity-preserving problems of autonomous underwater vehicles (AUVs) are investigated. For the sake of achieving these two goals more effectively, a novel distributed formation control scheme combined with artificial potential function is designed. Considering the disturbances of control input nonlinearities and the model uncertainties, we design a sliding mode controller based on RBF neural network. Then by Lyapunov method, we verify the stability of control strategy. At last, we establish a multi-AUVs model and simulate the control scheme with MATLAB. The effectiveness of the control strategy is testified by the simulations. |
| 源文献作者 | Beijing Institute of Technology ; Chinese Institute of Command and Control (CICC) ; IEEE Beijing Section ; Tongji University |
| 产权排序 | 3 |
| 会议录 | Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-0-7381-4657-7 |
| 源URL | [http://ir.sia.cn/handle/173321/30350]  |
| 专题 | 沈阳自动化研究所_智能检测与装备研究室 |
| 通讯作者 | Ma HJ(马宏军) |
| 作者单位 | 1.College of Information Science and Engineering, Northeastern University, Shenyang, China 2.Beijing Electro-Mechanical Engineering Institute, Science and Technology on Complex System, Conroland InelligentAgent Cooperation Laboratory, Beijing, China 3.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Chen, Bao,Ma HJ,Kang HB,et al. Multi-agent Distributed Formation Control Based on Improved Artificial Potential Field and Neural Network for Connectivity Preservation[C]. 见:. Beijing, China. October 15-17, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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