An Adaptive DE Algorithm Based Fuzzy Logic Anti-swing Controller for Overhead Crane Systems

In this paper, aiming at the under-actuated problem of the overhead crane systems, a fuzzy logic anti-swing controller is first designed according to operator experience. Moreover, for better configuring the parameters of the controller, an adaptive differential evolution with disturbance factor algorithm (ADE-D) is proposed by introducing the adaptive scaling factor, the dynamic crossover probability and disturbance factor. By implementing numeric experiment test, the results show that the adaptive differential evolution with disturbance factor algorithm outperforms the standard differential evolution algorithm and other improved differential evolution algorithms. Finally, the adaptive differential evolution with disturbance factor algorithm-based fuzzy logic anti-swing controller is simulated under different conditions and compared with other control methods; the results exhibit excellent robustness of control performance in positioning control and damping oscillation of payload.