Autonomous cooperative formation control of underactuated USVs based on improved MPC in complex ocean environment

A dual model predictive control (DMPC) method based on virtual trajectory is proposed in this paper, in order to achieve autonomous cooperative formation control of underactuated unmanned surface vehicles (USVs) in complex ocean environment. Firstly, the formation tracking error model of the USVs is designed, and considering the large initial state tracking error of USVs, a virtual transition trajectory is put forward to guide the design of tracking controller. To solve the mutation problem caused by misalignment of the follower USV's desired trajectory in the early stage, an improved differential tracker is introduced into virtual leader USV to smooth the desired trajectory of the follower USV. In addition, a dual mode switching strategy is designed to decide when and how to quit the transition of the virtual USV. A nonlinear disturbance observer is introduced to compensate the complex marine environment interference. Finally, by introducing terminal penalty function and linear state feedback controller, the Lyapunov function is constructed to prove the control stability of the proposed model predictive control method in finite time domain, and the effectiveness and reliability of the proposed method are verified by simulation experiments.

Automated summary

In this paper, a dual model predictive control (DMPC) method based on virtual trajectory is proposed for autonomous cooperative formation control of underactuated unmanned surface vehicles (USVs) in complex ocean environment. The method includes the design of formation tracking error model, virtual transition trajectory, improved differential tracker, dual mode switching strategy, nonlinear disturbance observer, terminal penalty function, linear state feedback controller, and Lyapunov function. Simulation experiments are performed to verify the effectiveness and reliability of the proposed method.