Nonlinear antiswing control for shipboard boom cranes with full state constraints

Abstract

A nonlinear energy-based controller and a Lyapunov-based model predictive control (MPC) technology are constructed in sequence for shipboard boom cranes, while taking full state constraints into account. The mathematical model is firstly transformed to ease the explicit influences of ship rollings on the desired positions and payload swings. Barrier Lyapunov functions (BLFs) are then involved in the energy-based controller to deal with different types of state constraints, in which constraints with positive bounds are also effectively tackled with a modified BLF. By adding a contractive constraint with the energy-based controller in traditional MPC framework, Lyapunov-based MPC is then established, in which the recursive feasibility and stability is ensured effectively and easily. Asymptotical stability of two controllers is analyzed and guaranteed in theory, respectively. Compared with the energy-based controller, control performance is improved and enhanced by the Lyapunov-based MPC through solving the optimal control problem. Simulations are finally implemented, and comparisons are also carried out to demonstrate the effectiveness and features of the established controllers in this paper.