Composite finite-time adaptive anti-disturbance control for dynamic positioning of vessels with output constraints

Abstract

Considering the high-complexity of offshore engineering and the limited operating time window in practice, the demands on the accuracy and performance of the dynamic positioning (DP) control system have been increased dramatically. However, the uncertainties caused by hydrodynamic variations and unknown environmental disturbances will decay the DP control performance. This study proposes a fast and precise composite control strategy for the DP of vessels in the presence of uncertainties and disturbances. To compensate for the uncertainties and disturbances, a finite-time adaptive disturbance observer (FADO) is constructed, in which an improved adaptive neural network technique is integrated. Then, a composite finite-time adaptive control strategy with prescribed output constraints is proposed. It is proved that both the positioning error and the compensation error will converge in finite time, and the positioning error will never violate its constraints. In addition, a joint high-fidelity simulation framework is developed to simulate the motion response of vessels under the DP control strategies and wave loads, through cross-platform interaction between robot operating system (ROS) and hydrodynamic programs. Thus, the control performance and complex hydrodynamics can be further realistically simulated in time domain. Finally, numerical simulations and high-fidelity simulations illustrate the effectiveness and superiority of the proposed DP control strategy.