Quadratic programming-based autonomous cruise control of an intelligent tugboat

Abstract

To address the multi-objective control problem of autonomous cruising, collision avoidance, and input constraints in intelligent tugboats, a quadratic programming-based autonomous cruise control method is proposed. The method enables the tugboat to reach the target location with prescribed speed, heading, and path while rigorously avoiding collisions within its actuation limits. First, a desired control input is derived using back-stepping and sliding mode control to ensure asymptotic stability of the tracking error. Second, based on Nagumo’s theorem, the positional constraints for safe collision avoidance of the tugboat are equivalently transformed into input constraints, effectively preventing any collisions with other vessels. Third, a unified controller is synthesized using a quadratic programming approach to optimally balance cruising control, collision avoidance, and input limitations. Finally, simulation results demonstrate that the proposed quadratic programming-based autonomous cruise control method enforces the prescribed safety distance and actuator limits, while avoiding large or persistent deviations from the reference trajectory and allowing the desired speed and heading to be re-established rapidly after the avoidance maneuver.