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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.
Highlights An energy-based controller is independently developed for shipboard boom cranes. The asymmetrical constraints on all states are strictly respected and asymptotic stability is guaranteed by embedding BLFs in the Lyapunov function and controller. To the best of our knowledge, Lyapunov-based MPC is firstly applied to shipboard boom cranes while tackling full state constraints. The recursive feasibility and asymptotic stability are ensured by taking energy-based controller as initial guesses and contractive constraints. Two groups of numerical simulations are implemented to demonstrate the effectiveness.
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.
Highlights An energy-based controller is independently developed for shipboard boom cranes. The asymmetrical constraints on all states are strictly respected and asymptotic stability is guaranteed by embedding BLFs in the Lyapunov function and controller. To the best of our knowledge, Lyapunov-based MPC is firstly applied to shipboard boom cranes while tackling full state constraints. The recursive feasibility and asymptotic stability are ensured by taking energy-based controller as initial guesses and contractive constraints. Two groups of numerical simulations are implemented to demonstrate the effectiveness.
Nonlinear antiswing control for shipboard boom cranes with full state constraints
Cao, Yuchi (Autor:in) / Li, Tieshan (Autor:in)
Applied Ocean Research ; 146
11.03.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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