Containment control of multiple unmanned surface vessels with NN control via reconfigurable hierarchical topology

Wei Liu; Fei Teng; Huiyu Xiao; Chen Wang

doi:10.3389/fncom.2023.1284966

Containment control of multiple unmanned surface vessels with NN control via reconfigurable hierarchical topology

Front Comput Neurosci. 2023 Oct 19:17:1284966. doi: 10.3389/fncom.2023.1284966. eCollection 2023.

Authors

Wei Liu¹, Fei Teng², Huiyu Xiao², Chen Wang¹

Affiliations

¹ School of Navigation, Dalian Maritime University, Dalian, China.
² College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.

Abstract

This paper investigates the containment control of multiple unmanned surface vessels with nonlinear dynamics. To solve the leader-follower synchronization problem in a containment control system, a hierarchical control framework with a topology reconfiguration mechanism is proposed, and the process of containment control is converted into the tracking of a reference signal for each vessel on its respective target heading by means of the light-of-sight (LOS) guidance. In a control system, the neural networks (NNs) are adopted to consider the uncertainty. In the follower layer, a connectivity controller with a topology reconfiguration mechanism is embedded, to change the converging positions of followers so as to avoid collision within the system, and to maintain the system connectivity when the communication equality is poor. The effectiveness of the hierarchical control framework proposed in this paper is valid by simulation.

Keywords: LOS guidance; containment control; hierarchical communication topology; neural network control; topology reconfiguration.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Zhejiang Lab Open Research Project (No. K2022QA0AB03), National Natural Science Foundation of China (Nos. 52371360, 52201407, and 51939001), High Level Talents Innovation Support Plan of Dalian (Young Science and Technology Star Project) (No. 2021RQ058), Funds for the Central Universities (No. 3132023147), and Fundamental Research Funds for the Central Universities (No. 3132023103).