Intelligent Sliding Mode Control of an Overhead Container Crane

TL;DR

This paper presents an adaptive fuzzy sliding mode control approach for an overhead container crane, enhancing robustness and accuracy in set-point regulation and trajectory tracking through experimental validation.

Contribution

It introduces an innovative combination of sliding mode control with fuzzy inference for improved performance in crane control systems.

Findings

Successful implementation on a scaled experimental crane

Enhanced robustness against uncertainties and disturbances

Improved stabilization and trajectory tracking performance

Abstract

In this contribution, an intelligent controller is proposed for an underactuated overhead container crane subject to both parameter uncertainties and unmodeled dynamics. The adopted approach is based on the sliding mode method to confer robustness against modeling inaccuracies and external disturbances. Additionally, an adaptive fuzzy inference system is embedded within the control law to improve set-point regulation and trajectory tracking. In order to evaluate the performance of the proposed intelligent scheme, the control law was implemented and tested in a 1:6 scale experimental container crane, available at the Institute of Mechanics and Ocean Engineering at Hamburg University of Technology. The obtained experimental results demonstrate not only the feasibility of the proposed scheme, but also its improved efficacy for both stabilization and trajectory tracking problems.