Fixed-time neural network trajectory tracking control for underactuated surface vessels

A disturbance observer based intelligent control for nonstrict-feedback nonlinear systems

Neural adaptive output feedback tracking control of underactuated AUVs

This article investigates the distributed event‐triggered affine formation maneuver control problem for multiple underactuated surface vessel (USV) systems with positive minimum inter‐event times (MIET). Unlike common formation control methods that only ensure the formation system to keep a fixed geometric shape, the proposed scheme enables multiple USVs maneuver as a group in translation, shearing, rotation, or combinations of them. The proposed control strategy is composed of two parts. First, a distributed event‐triggered observer (DETO) is proposed to observe the time‐varying target formation under the lack of global leaders' information and govern the inter‐vessel communications among the formation group. Besides, the MIET of the designed communication strategy is proved to be strictly positive and computable from formation configurations and control parameters. With these guarantees, the maximum communication frequency can be known in advance. Then, upon the DETO signals, the adaptive local tracking controller is subsequently synthesized for each vessel to realize the target formation track. Rigorous theoretical analysis and simulation results are finally conducted to verify the validness and effectiveness of the proposed algorithm.

Distributed observer based event‐triggered affine formation maneuver control for underactuated surface vessels with positive minimum inter‐event times

Finite-time time-varying formation control for marine surface vessels

Adaptive prescribed performance tracking control for underactuated autonomous underwater vehicles with input quantization

Finite-time distributed formation control for multiple unmanned surface vehicles with input saturation

This paper provides a model-parameter-free control strategy for the trajectory tracking problem of the autonomous underwater vehicle exposed to external disturbances and actuator failures. Two control architectures have been constructed such that the system states could be forced to the desired trajectories with acceptable performance. By combining sliding mode control (SMC) technology and adaptive algorithm, the first control architecture is developed for tracking missions under healthy actuators. Taking actuator failures scenario into account, system reliability is improved considerably by the utilization of a passive fault-tolerant technology in the second controller. Benefitting from properties of Euler–Lagrange systems, the nonlinear dynamics of the underwater vehicles could be handled properly such that the proposed controllers could be developed without model parameters. Finally, the validity of the proposed controllers is demonstrated by theoretical analysis and numerical simulations.

Cheng Zhu

Papers

Adaptive prescribed performance tracking control for underactuated autonomous underwater vehicles with input quantization

Finite-time distributed formation control for multiple unmanned surface vehicles with input saturation

Adaptive model-parameter-free fault-tolerant trajectory tracking control for autonomous underwater vehicles.

Saturated approximation-free prescribed performance trajectory tracking control for autonomous marine surface vehicle

Finite-time time-varying formation control for marine surface vessels