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.

针对高架起重机系统驱动不足的问题，本文首先根据操作人员的经验设计了模糊逻辑防摆控制器。此外，为了更好地配置控制器参数，通过引入自适应比例因子，动态交叉概率和干扰因子，提出了一种带有干扰因子的自适应差分进化算法（ADE-D）。通过数值实验测试，结果表明，采用干扰因子算法的自适应差分进化算法优于标准差分进化算法和其他改进的差分进化算法。最后，在不同条件下，模拟了基于扰动因子算法的自适应差分进化模糊逻辑防摆控制器，并与其他控制方法进行了比较。结果表明，在定位控制和有效载荷阻尼振荡方面，控制性能具有出色的鲁棒性。