Adaptive Control for Marine Vessels Against Harsh Environmental Variation
This work addresses the challenge of safe and stable operation for marine vessels like accommodation vessels in unpredictable sea conditions, representing an incremental improvement in domain-specific control methods.
The paper tackles the problem of dynamic positioning for marine vessels under harsh environmental variations, such as unknown hydrodynamic forces and input time delays, by proposing a robust control scheme with a sea state observer and neural network compensator, resulting in demonstrated boundedness of closed-loop signals through simulation studies.
In this paper, robust control with sea state observer and dynamic thrust allocation is proposed for the Dynamic Positioning (DP) of an accommodation vessel in the presence of unknown hydrodynamic force variation and the input time delay. In order to overcome the huge force variation due to the adjoining Floating Production Storage and Offloading (FPSO) and accommodation vessel, a novel sea state observer is designed. The sea observer can effectively monitor the variation of the drift wave-induced force on the vessel and activate Neural Network (NN) compensator in the controller when large wave force is identified. Moreover, the wind drag coefficients can be adaptively approximated in the sea observer so that a feedforward control can be achieved. Based on this, a robust constrained control is developed to guarantee a safe operation. The time delay inside the control input is also considered. Dynamic thrust allocation module is presented to distribute the generalized control input among azimuth thrusters. Under the proposed sea observer and control, the boundedness of all the closed-loop signals are demonstrated via rigorous Lyapunov analysis. A set of simulation studies are conducted to verify the effectiveness of the proposed control scheme.