Data-Driven Model-Free Adaptive Positioning and Anti-Swing Control for Bridge Cranes

In the positioning and anti-swing control of bridge crane, a model-free adaptive (MFAC) based on data-driven is proposed in order to eliminate dependence controller design model influence unmodeled dynamics uncertain disturbances performance. Only using input output data crane system, virtual full format dynamic linearized nonlinear system obtained through modeling method. On basis this model, law pseudo-Jacobian matrix estimation algorithm are designed according optimization theory under constraint conditions. The stability closed loop convergence error analyzed proved by Lipschitz condition inequality theory. effectiveness strategy for cranes verified simulated simulation experimental platform crane. results show that method feasible has good anti-disturbance performance robustness.