Payload swing control of a tower crane using a neural network–based input shaper

Abstract

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.

Spatial transportation of the beam on a bifilar fastening

“…In a number of works, a model of a spherical pendulum with a movable suspension point is considered a 3D model for cargo movement by a crane, taking into account the elastic properties of the rope and the action of an external wind load [21][22][23][24][25][26][27][28][29][30][31][32][33].…”

Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment

“…Moreover, feedforward shapers, namely, a command shaper [27][28] and a smoother [29][30][31], with different design approaches have been investigated. Improved input shapers have also been proposed for an overhead crane [32] and a tower crane [33].…”

Swing Characteristics and Vibration Feature of Tower Cranes under Compound Working Condition

“…Ebrahimi et al developed a method to estimate the swing angle using load cell sensors [15]. e performance evaluation experiment used a laboratory tower crane with cable length variations and under simultaneous tangential and radial crane motions [16]. Fatehi et al developed a dynamic model that includes both the flexible cable's transverse vibrations and large swing angles while the trolley moves horizontally [17].…”