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

作     者：Sun, Zhe Ling, Yawen Qu, Hongbo Xiang, Feng Sun, Zhixin Wu, Fan 

作者机构：Nanjing Univ Posts & Telecommun Post Ind Technol Res & Dev Ctr State Posts Bur Internet Things Technol Post Big Data Technol & Applicat Engn Res Ctr Jia Nanjing 210023 Peoples R China YuanTong Express Shanghai 201705 Peoples R China Tuskegee Univ Comp Sci Dept Tuskegee AL 36088 USA 

出 版 物：《INTERNATIONAL JOURNAL OF FUZZY SYSTEMS》 (Int. J. Fuzzy Syst.)

年 卷 期：2020年第22卷第6期

页      面：1905-1921页

核心收录：

基　　金：Natural Science Foundation of China [61672299, 61972208, 61602259, 61701251, 61803213, 61972211] Natural Science Foundation of the Jiangsu Higher Education Institutions of China [18KJB520035, 18KJB510016] National Engineering Laboratory for Logistics Information Technology, YuanTong Express Co. LTD 

主　　题：Overhead crane systems Fuzzy control Fusion function Differential evolution algorithm 

摘      要：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.