船用起重机自适应神经网络滑模防摆控制

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中图分类号：U664.4；U653.921；TP273 文献标志码：A

Abstract：Aiming at the problem of underactuated shipborne jib cranes subjected to persistent uncertain upper-bound disturbances，an adaptive radial basis function neural network （ARBNN） hierarchical sliding mode control（HSMC）method（called ARBFNN-HSMC method） is proposed. The dynamical model of the ship-crane-payload complex system affcted by sustained sea waves is established using the Lagrangian method and converted into the standard form of an underactuated system. HSMC method is employed to design the control law，compensating for system parameter perturbations.ARBFNN is used to approximate and compensate for disturbances with uncertain upper bounds caused by external nonlinear disturbances. The asymptotic stability of the system is proven using the Lyapunov function. Simulation results demonstrate that the proposed method exhibits strong robustness under persistent unknown disturbances and effectively achieves the dual objectives ofpayload positioning and oscillation elimination.

Key words ： shipborne crane ;anti-sway control； underactuated system； hierarchical sliding mode control（HSMC）；adaptive radial basis function neural network （ARBNN）

0 引言

海上船用臂架起重机作为海洋工程领域的核心装备之一，广泛应用于货物转运、海底隧道搭建、沉船打捞、跨海建桥等项目中的水下吊装作业和水下补给等[1-2]。（剩余7923字）