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. •A novel ETMPF control scheme with the SETM is proposed to avoid the dependence on continuous control command with a simpler structure and lower computational burden.•A DETM is further developed to extend the triggering interval and the MIET of the DETM can be strictly positive and computable.•The network bandwidth requirement of the proposed control scheme can be known prior.