摘要
本文考虑利用多个自主式水下航行器(AUV)实现流场估计,提出了一种基于树型网络的分布式方法来估计水下流场.在本文中,借助绝对运动积分误差和相对运动积分误差,流场估计问题被描述为求解一个以未知流场为变元的非线性方程组.继而本文在多AUV系统内建立一个低通讯成本的树型网络,并在该网络上运行一种分布式算法以求解与流场估计相关的非线性方程组.在该算法中,每个AUV将当前的流场估计值连续地投影到自身拥有的约束方程的解集中,并通过扩散和池化两个步骤在树型网络间传递流场估计值.本文证明了上述算法的收敛性,并通过仿真实验验证了所述分布式协同流场估计方法的有效性.
This paper considers the use of multiple autonomous underwater vehicles(AUVs) to estimate the fiow field,and proposes a distributed method based on a tree-structure network to estimate the underwater fiow field. In this paper, the fiow field estimation problem is described as solving a nonlinear equation system with the unknown fiow field as argument using absolute motion-integration error and relative motion-integration error. Then this paper establishes a tree-structure network with low communication cost in the multi-AUV system to run a distributed algorithm to solve the nonlinear equation system related to the fiow field estimation. In this algorithm, each AUV continuously projects current fiow field estimation value to the solution set of its own constraint equations. And through the two steps of dispersion and pooling,the fiow field estimation value is transferred within the tree-structure network. This paper proves the convergence of the proposed algorithm, and the effectiveness of the distributed cooperative fiow field estimation method is verified through simulation experiments.
作者
何翌
郑荣濠
张森林
刘妹琴
HE Yi;ZHENG Rong-hao;ZHANG Sen-lin;LIU Mei-qin(College of Electrical Engineering,Zhejiang University,Hangzhou Zhejiang 310027,China;State Key Laboratory of Industrial Control Technology,Zhejiang University,Hangzhou Zhejiang 310027,China;Institute of Artificial Intelligence and Robotics,Xi’an Jiaotong University,Xi’an Shaanxi 710049,China)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2022年第11期2036-2046,共11页
Control Theory & Applications
基金
国家自然科学基金委员会–浙江两化融合联合基金(U1709203,U1909206,U1809212)
浙江省自然科学基金(LZ19F030002)
国家自然科学基金项目(61873235)
浙江省重点研发计划项目(2019C03109)资助。