Coordinated Control of Multiple Surface Unmanned Vehicle Clusters under the Influence of Wind Field and Tides
- Authors: Liu Y.1, Dang Z.1, Dai Z.1, Hao X.1, Cui Y.1, Gao H.1
- 
							Affiliations: 
							- School of Mathematics and Statistics, Qingdao University
 
- Issue: Vol 63, No 10 (2023)
- Pages: 1615-1615
- Section: Optimal control
- URL: https://rjpbr.com/0044-4669/article/view/664964
- DOI: https://doi.org/10.31857/S0044466923100101
- EDN: https://elibrary.ru/FPDRJY
- ID: 664964
Cite item
Abstract
This paper investigates the problem of coordinated control for multiple surface unmanned vehicles in a cluster under the influence of time-varying disturbances such as wind field and tides, based on state feedback controllers. With the rapid development of offshore cluster formation control technology, studying the cluster formation control problem of surface unmanned vehicles in multiple clusters under the influence of wind field and tides in complex and changing sea environments has important practical significance. This paper proposes a complete solution based on the Hamiltonian method. Firstly, each cluster is set to be located within a ellipsoidal virtual container throughout the entire motion process, and the trajectory of the virtual ellipsoid is used as an external state constraint for the cluster. Based on this, the dynamic equation of the system and the corresponding value function under the influence of wind field and tides on the sea surface are established, and the Hamilton–Jacobi–Bellman equation is used to solve the energy constraint and mutual avoidance between clusters and their members to obtain the optimal control and trajectory of each cluster. Finally, numerical simulation results demonstrate the effectiveness of the proposed method.
About the authors
Yanshan Liu
School of Mathematics and Statistics, Qingdao University
														Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
Zhiqing Dang
School of Mathematics and Statistics, Qingdao University
														Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
Zhaopeng Dai
School of Mathematics and Statistics, Qingdao University
														Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
Xinran Hao
School of Mathematics and Statistics, Qingdao University
														Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
Yan Cui
School of Mathematics and Statistics, Qingdao University
														Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
Hongwei Gao
School of Mathematics and Statistics, Qingdao University
							Author for correspondence.
							Email: dzpeng@amss.ac.cn
				                					                																			                												                								266071, Qingdao, Shandong, China						
References
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