Research Areas

A significant research effort has been devoted for the past 40 years to developing control strategies to improve efficiency and to guarantee the safety of cranes. In the field of modeling crane systems, the simplified model was used to proposed different control laws, from open-loop control to the closed-loop technique. However, this model seems to be not sufficient when cranes become larger and larger: the rope length is very long, and the payload is too heavy. Hence, the introduction of the distributed-mass model can become a potential solution, because it has the capability of describing exactly the system dynamics of cranes. In the field of developing crane control algorithms, the input shaping technique has shown an ability to control trolley position and also the sway motion of the payload. However, if the considered system has an uncertain parameter, control design based on the input shaping technique may not fulfill the goal. Linear control techniques were added to input-shaping-based strategies to overcome these shortcomings. Nonetheless, they are also not robust enough to allow for variations in the cable length, payload mass, and high operating speeds. Fuzzy logic control, sliding mode control, and adaptive control are the potential candidates for crane control. A combination of all these advanced methods can provide a significant control strategy thanks to its capability to guarantee system stability in the presence of uncertain parameters. Notwithstanding, it is addressed that the design of hybrid control strategies using these advanced techniques is not trivial.