Enhanced Control of Overhead Crane System Using First-Order Sliding Mode Control and Extended Kalman Filter Observer

Abstract

Overhead cranes are now highly automated devices, and numerous studies have been devoted to the design and implementation of automatic controllers to reduce residual vibrations during cargo change operations. Tipping over crane payloads seriously impairs their efficiency and safety. The reduced payload oscillations on a single pendulum crane with a point payload attached to the end of the cable brought significant improvements. On the other hand, the large payloads and the actual arrangement of the lifting mechanism can convert the crane into a double pendulum system with a distributed mass payload. Therefore, in this article, a nonlinear model is presented initially, after which it is linearized. Then, a robust First-Order Sliding Mode Controller (FOSMC) will be developed for a spreading system capable of automatically driving the container to the desired angle while eliminating the residual oscillations caused by the cable. To accurately estimate the states of the system, such as the angle of the cable and the angle of the payload (spreader and container), an Extended Kalman Filter (EKF) observer is used. The simulation results, obtained using Matlab/Simulink, show that the proposed approach provides accurate and stable control of the system with improved static and dynamic performances in terms of eliminating the position error for the angle of the cable, improving the angle stability with a small overshoot, ameliorating the response time, and canceling the estimation error of the state variables. Consequently, this research contributes to the enhancement of overhead crane automation by addressing the obstacles arising from payload oscillation.