Modelling and Fuzzy Logic Control of an Underactuated Tower Crane System

Tower crane is one of the flexible maneuvering systems that has been applied pervasively as a powerful big-scale construction machine. The under-actuated tower crane system has nonlinearity behavior with a coupling between translational and slew motions which increases the crane control challenge.  In practical applications, most of the tower cranes are operated by a human operator which lead to unsatisfactory control tasks. Motivated to overcome the issues, this paper proposes a fuzzy logic controller based on single input rule modules dynamically connected fuzzy inference system for slew/translational positioning and swing suppressions of a 3 degree-of-freedom tower crane system. The proposed method can reduce the number of rules significantly, resulting in a simpler controller design. The proposed method achieves higher suppressions of at least 56% and 81% in the overall in-plane and out-plane swing responses, respectively as compared to PSO based PID+PD control.