Adaptive Leader-Follower Formation Control of Under-actuated Surface Vessels with Model Uncertainties and Input Constraints

Abstract

This paper deals with the leader-follower formation control of underactuated autonomous surface vehicles in the presence of model uncertainties and input constraints. In a leader-follower formation, an autonomous surface vehicle (ASV) called leader tracks a pre-described trajectory and other ASVs called followers that are controlled to follow the leader with a desired distance and desired relative bearing. To this end, some adaptive robust techniques are adopted to guarantee the robustness of the closed-loop system against model uncertainties, external disturbances, and input saturation constraints. Based on the Lyapunov synthesis, it is proven that with the developed formation controllers, the closed-loop system is stable and all the formation errors converge to a small neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed method.

Distributed Leader-Follower Formation Control for Autonomous Vessels based on Model Predictive Control

“…In the fourth approach, the leader-follower approach, a designated leader is followed by *This research is supported by the Amsterdam Institute for Advanced Metropolitan Solutions (AMS Institute), the Researchlab Autonomous Shipping (RAS) at Delft University of Technology, the European Regional Development Fund, as part of the Interreg North Sea Region project AVATAR, and by the project "GasDrive: Minimizing emissions and energy losses at sea with LNG combined prime movers, underwater exhausts and nano hull materials" (project 14504) of the Netherlands Organization for Scientific Research (NWO), domain Applied and Engineering Sciences (TTW). the followers respecting user-defined distances between the leader and followers [14], [15], [16]. The suitability of each approach depends on the purpose of the application.…”

“…The Backstepping approach is proposed in [10] to hold a desired intership formation pattern in a group of autonomous surface vehicles. Neural Networks are used in [16] to control a group of vessels using leader-follower formation control. In [6], Model Predictive Control (MPC) is applied to a group of quadrotors that is able to avoid dynamic obstacles.…”