An Anti-Swing Closed-Loop Control Strategy for Overhead Cranes

Abstract

The payload swing of an overhead crane needs to be controlled properly to improve efficiency and avoid accidents. However, the swing angle is usually very difficult to control to zero degrees or for it to even remain within an acceptable range because the overhead crane is a complex nonlinear underactuated system, especially when the actual working environment is accompanied by strong disturbances and great uncertainty. To resolve this, a real-time anti-swing closed-loop control strategy is proposed that considers external disturbances. The swing angle is measured in time and it functions with the load displacement as feedback inputs of the closed-loop system. The nonlinear model of the crane is simplified by a linear system with virtual disturbances, which are estimated by the equivalent input disturbance (EID) method. Both simulation and experimental results for a 2-D overhead crane system are investigated to illustrate the validity of the proposed method.

Shipyard Crane Modeling Methods

“…Complete nonlinear model of the crane with constant rope length is described with using eight state equations (Aksjonov et al 2015;Aksjonov et al 2016). The same crane system with varying rope length is described using ten nonlinear state equations (Ma et al 2018). But the model is verified for a single rope sling.…”

LMI based antiswing adaptive controller for uncertain overhead cranes

“…Consider the following theorem: Theorem: Assume that the LMI condition (9) is feasible for some P and the controller gain K is given by (10), the adaptive law is given by (11). Then the controller u1 can make the error dynamics x converge to zero.…”

“…However, in general, the open-loop control system can not guarantee the good performance in the case of system uncertainties and external disturbances. Therefore, many closed-loop control techniques are applied to the overhead crane system to improve the performance such as nonlinear feedback [7][8][9][10][11], partial feedback linearization [12,13], fuzzy logic control [14][15][16][17], sliding mode control [18][19][20][21] and so on.…”

Real-Time Robust and Optimized Control of a 3D Overhead Crane System

“…Discrete-time model predictive control (MPC) was utilized for a linearized model of a two-dimensional (2D) overhead crane to maintain load swings within acceptable range and avoid actuators saturation using constraint optimization nature in MPC [8]. Similar use of MPC on a linearize model of an overhead crane with virtual disturbance estimation was recently proposed in [9].…”