Adaptive prescribed-time containment control for multiple unmanned surface vehicles with uncertain dynamics and actuator dead-zones

This paper investigates the containment control problem of multiple unmanned surface vehicles (USVs) with directed communication topology. The unknown dynamics, external disturbances and actuator dead-zones of each USV are taken into account. Firstly, an event-triggered quantized (ETQ) control strategy and an improved prescribed-time control technique are combined, such that a balance is achieved between reducing the channel burden and ensuring control performance. Then, with the aid of backstepping method, finite-time differentiators, neural networks and parametric adaptive techniques, a fully-distributed adaptive containment controller is developed. The idea of single-parameter learning and estimating the upper bound of disturbances greatly reduce the calculation of the controller. Importantly, the degradation of the control performance caused by saving channel resources and reducing calculation is not worth worrying about, thanks to the performance prescribed control scheme. It is proved that all signals in the closed-loop system are bounded and the containment error of the multi-USV system is semi-globally practically finite-time stable. Finally, the effectiveness of the proposed controller was verified by simulations of 1:70 scale ship models.

Automated summary

This paper investigates the containment control problem of multiple unmanned surface vehicles (USVs) with directed communication topology. It proposes a fully-distributed adaptive containment controller that combines an event-triggered quantized (ETQ) control strategy and an improved prescribed-time control technique. The controller utilizes backstepping method, finite-time differentiators, neural networks, and parametric adaptive techniques. It is shown that the controller effectively reduces the calculation and channel burden while maintaining control performance.