Collision-free output-feedback super-twisting control of robotic surface vehicles for coordinated path following with experiments

Abstract

This paper addresses the coordinated path following (CPF) control of robotic surface vehicles (RSVs) in the presence of multiple obstacles and lumped disturbances over a resource-constrained wireless network. A collision-free output-feedback super-twisting control architecture is proposed for CPF without using velocity measurements. Specifically, robust exact differentiator observers are designed at first to recover the unmeasured velocities, and estimate the lumped disturbances, simultaneously. Next, anti-disturbance output-feedback super-twisting control laws are proposed to achieve individual path following in earth-fixed reference frame, and an adaptive potential field with a user-defined collision hazard degree is introduced to avoid the collisions with obstacles. To reduce the network traffic, self-triggered path updating laws are then designed for avoiding the continuous transmitting and listening of neighboring RSVs. The stability analysis shows that the closed-loop system is input-to-state stable outside the collision avoidance region, and Zeno behavior will not happen. Experiments are finally conducted to validate the efficacy of the proposed collision-free output-feedback super-twisting control method for the self-triggered CPF of RSVs.