Event-Based Affine Formation Maneuver Control for Multi-ASV Systems With Input Saturation
Dingze Zhang, Yue Yang, Kezhong Liu, Tieshan Li
Abstract
This research investigates the problem of event-based affine formation maneuver control for multi-Autonomous Surface Vehicle (ASV) systems. To date, most studies of ASV formation have only focused on static formation configuration. However, in practical applications, ASVs need to change formation maneuvering to accomplish various tasks, such as obstacle avoidance and maritime patrol. Addition, multi-ASV systems are constrained by environmental disturbances, limited communication resources, and input saturation. To deal with these constraints, a novel formation maneuver control strategy for multi-ASV systems is proposed. First, to achieve formation maneuvering in multi-ASV systems, an affine formation maneuver controller based on a stress matrix is designed. Second, radial basis function neural networks are deployed to reduce the influence of nonlinear term on multi-ASV systems. An event-triggered mechanism is used to decrease the frequency of information transmission, thereby conserving communication resources. Finally, the stability and the Zeno behavior of the system are analyzed. The simulation demonstrates that the control strategy proposed in this research enables multi-ASV systems to complete formation maneuver tasks.