Robust Moving Path Following Control for Robotic Vehicles: Theory and Experiments

Abstract

This letter addresses the moving path following (MPF) motion control problem that consists of steering a robotic vehicle along a specified geometric path expressed with respect to a moving target frame. External disturbances that depend on the operational environment such as maritime currents, wind, or rough terrain can affect the vehicle motion in a variety of ways. Furthermore, imperfections and simplifications of the vehicle model can also lead to unknown disturbances. One way to overcome this problem is by designing robust controllers to perform the task. Existing literature on MPF control does not consider these disturbances and further assume that the linear and angular velocity of the target frame is known. In this letter, these assumptions are relaxed through the design of robust MPF control schemes. To this end, two robust control strategies are proposed to solve the MPF control problem for a robotic vehicle with actuation constraints and bounded disturbances. Using Lyapunov-based arguments, both controllers are proven to be globally asymptotically stable with respect to the origin of the MPF error. Experimental results using autonomous underwater vehicles demonstrate the viability of the proposed control schemes for applications in a real world environment.