Variable output model-free adaptive heading control method for unmanned surface vehicle

Objective Aiming at the uncertainty of model perturbation and external interference in unmanned surface vehicles (USVs), an improved model-free adaptive control (MFAC) method suitable for the heading control of USVs is proposed.

Methods Based on the existence of non-self-balancing characteristics in the heading control subsystems of USVs, this study directly discusses the control problem of the heading control subsystems of USVs under uncertain influences using the compact form dynamic linearization-based MFAC (CFDL-MFAC). The historical input items are introduced into the standard control criteria, and a variable output CFDL-MFAC (VCFDL-MFAC) is proposed to weaken the integral effect existing in the heading control subsystems of USVs. Finally, the simulation of USV heading control using the proposed method is carried out and a field-test with regard to validity for operation on board a Dophin IB small USV is conducted.

Results The results show that compared to the standard CFDL-MFAC method and PID method, the heading control of the VCFDL-MFAC method is more stable.

Conclusions This study can provide a USV heading control algorithm with good adaptability and robustness that is insensitive to environmental disturbances and model perturbations.