This paper proposes an input shaping technique for efficient payload swing control of a tower crane with cable length variations. Artificial neural network is utilized to design a zero vibration derivative shaper that can be updated according to different cable lengths as the natural frequency and damping ratio of the system changes. Unlike the conventional input shapers that are designed based on a fixed frequency, the proposed technique can predict and update the optimal shaper parameters according to the new cable length and natural frequency. Performance of the proposed technique is evaluated by conducting experiments on a laboratory tower crane with cable length variations and under simultaneous tangential and radial crane motions. The shaper is shown to be robust and provides low payload oscillation with up to 40% variations in the natural frequency. With a 40% decrease in the natural frequency, the superiority of the artificial neural network–zero vibration derivative shaper is confirmed by achieving at least a 50% reduction in the overall and residual payload oscillations when compared to the robust zero vibration derivative and extra insensitive shapers designed based on the average operating frequency. It is envisaged that the proposed shaper can be further utilized for control of tower cranes with more parameter uncertainties.
This paper investigates the performance of input shaping techniques for sway control of a rotary crane system. Unlike the conventional optimal controllers, input shaping is simple to design and cost effective as it does not require feedback sensors. Several input shapers were implemented and their performances were compared which are useful for future sway control designs. A nonlinear model of the system was derived using the Lagrange’s energy equation. To investigate the performance and robustness of input shaping techniques, zero vibration (ZV), zero vibration derivative (ZVD), zero vibration derivative-derivative (ZVDD) and zero vibration derivative-derivative-derivative (ZVDDD) were proposed with a constant cable dimension. Level of reduction of the payload sway was used to assess the control performance of the shapers. Simulation and real time experimental results have shown that ZVDDD with an average sway reduction of 88% has the highest level of sway reduction and robustness to modeling errors as compared to 85%, 80% and 65% for ZVDD, ZVD and ZV respectively.
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