单向拓扑下基于DMPC与改进APF的水面无人艇编队运动控制算法

A Formation Motion Control Algorithm of Unmanned Surface Vehicles Based on DMPC and Improved APF Under Unidirectional Topologies

多水面无人艇编队运动控制是多水面无人艇智能化的核心技术,也是当前研究的热点。重点讨论了编队部分成员无法获得编队平衡先验信息条件下的水面无人艇编队运动控制问题。首先,针对编队先验信息不平衡条件下无人艇编队保持困难的问题,将领航–跟随结构与分布式模型预测控制算法结合,通过设定通信优先级和单向拓扑结构,在分布式模型预测控制算法中引入假设状态空间和平衡状态空间,以实现部分跟随者无法获取编队平衡先验信息情况下的无人艇编队保持;其次,针对编队航行过程中障碍物规避安全性不足的问题,将改进的人工势场法与模型预测控制相结合,设计了无人艇自主避障控制器,提升了编队航行过程的安全性;最后,通过仿真平台对所提方案的可行性进行了验证。所提方法可以为进一步研究复杂环境下多水面无人艇编队运动控制提供参考。

The formation motion control of multi-Unmanned Surface Vehicles(USV) is the core technology for the intelligence of multi-USVs, and it is also a current research hotspot. The problem of formation maintenance in multi-USV formation motion control is focused on in this paper, which is discussed under the condition that some members cannot obtain prior information on formation balance. Firstly, the Leader-Follower structure is combined with distributed model predictive control. The hypothetical state space and equilibrium state space are introduced into the model predictive control algorithm by setting up communication priorities and unidirectional topology. Then, the cost function is designed, and the sequential quadratic programming algorithm is used to solve the minimum cost. So that it is realized that the formation maintenance of multi-USVs when some followers cannot obtain the prior information of the formation balance. Secondly, for avoiding obstacles during formation motion, the improved artificial potential field method and model predictive control are combined to complete the design of the autonomous obstacle avoidance controller for USV. Based on the above work, the process of formation control of USV is proposed. Finally, the feasibility of the proposed method is verified by the simulation experiment. The proposed method can provide a reference for further research on the formation motion control of multi-USVs in some complex environments.