Abstract
The paper proposes a new approach to efficiently control a three-dimensional overhead crane with 6 degrees of freedom (DoF). Most of the works proposing a control law for a gantry crane assume that it has five output variables, including three positions of the trolley, bridge, and pulley and two swing angles of the hoisting cable. In fact, the elasticity of the hoisting cable, which causes oscillation in the cable direction, is not fully incorporated into the model yet. Therefore, our work considers that six under-actuated outputs exist in a crane system. To design an efficient controller for the 6 DoF crane, it first employs the hierarchical sliding mode control approach, which not only guarantees stability but also minimizes the sway and oscillation of the overhead crane when it transports a payload to a desired location. Moreover, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by utilizing the fuzzy inference rule mechanism, which results in efficient operations of the crane in real time. More importantly, stabilization of the crane controlled by the proposed algorithm is theoretically proved by the use of the Lyapunov function. The proposed control approach was implemented in a synthetic environment for the extensive evaluation, where the obtained results demonstrate its effectiveness.
Highlights
Overhead crane systems have been playing a crucial role in many applications from industries or factories to transportation [1,2,3,4,5]
We propose to exploit the fuzzy inference rule system to adaptively infer the parameters of Electronics 2022, 11, 713 the hierarchical SMC (HSMC) scheme over time
In order to demonstrate effectiveness of our proposed approach, the adaptive fuzzy hierarchical sliding mode controller (FuzzyHSMC), in controlling the 3D overhead crane with 6 degrees of freedom (DoF), we conducted the experiments in the synthetic simulation environment
Summary
Overhead crane systems have been playing a crucial role in many applications from industries or factories to transportation [1,2,3,4,5]. Choosing an improper parameter for the HSMC controller is probably due to imprecision and imperfect information in the crane This is very likely in practice, since the under-actuated crane systems are constrained by their highly complicated nonlinearities and uncertainties. It can be seen that there are up to 6 DoF in one 3D overhead crane, where there are three under-actuated output variables including two swing angles and oscillation of the hoisting cable in x, y, and the cable directions, respectively. It is noted that in this work, matrices and vectors are expressed in square brackets [·] or parentheses (·), while long expressions are encapsulated in braces {·}
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
