An Effective Neuro-adaptive Control Approach for Underwater Flexible Cranes With Uncertainties

With the exploitation of marine resources, the underwater crane system has become an indispensable transportation tool on the sea; however, its control problems are still open. For this type of crane system, due to the flexible characteristics of its payload, the system dynamic model is very complex; meanwhile, the payload transverse deviation is amplified due to the hydrodynamic force, resulting in residual vibration of the payload. Moreover, the bad operating environment leads to many uncertain disturbances, bringing more challenges to its control issues. To solve the problems mentioned above, an effective neuro-adaptive controller is designed in this paper. Specifically, without linearizing the obtained nonlinear model, the controller is designed through a two-layer neural network, and the approximation error of the neural network is also eliminated. Then, we use Lyapunov stability theory to prove that the controller can make all state variables converge to their desired values. As far as we know, this paper yields the first complete control solution for the control problem of the underwater flexible crane system, which can well deal with the complex nonlinear characteristics caused by the flexible payload, achieve excellent control performance, and improve the robustness of the system with respect to parameter uncertainties and external disturbances. Finally, through a series of simulation results, it is verified that the proposed method can make the trolley arrive at the desired position accurately and suppress the flexible payload's residual vibration effectively.

Automated summary

An effective neuro-adaptive controller is designed for the control problem of the underwater flexible crane system, utilizing a two-layer neural network design without linearizing the nonlinear model, and proving the controller's effectiveness through Lyapunov stability theory. Simulation results verify that the proposed method can accurately reach the target position and effectively suppress the flexible payload's vibration.