Event-triggered model-parameter-free trajectory tracking control for autonomous underwater vehicles

This article focuses on the event-triggered model-parameter-free (ETMPF) control problem for autonomous underwater vehicles (AUVs). To realize the trajectory tracking goal under internal model parameter uncertainties and external disturbances, the ETMPF control law is firstly presented via the properties of Euler-Lagrange systems. In the designed ETMPF control law, a static event-triggered mechanism (SETM) is developed to reduce its communication burden with actuators. Then, by introducing internal dynamic variables for the SETM, a dynamic event-triggered mechanism (DETM) is further developed. Compared to the SETM, the maximum triggering frequency under the DETM is computable and can be adjustable by tuning control parameters, which makes it applicable to more serve network resource-limited scenarios. Finally, the effectiveness of the designed two ETMPF control schemes is demonstrated through theoretical analysis and simulation results.