基于神经网络算法的桥式起重机防摇摆控制*

作者：丁瑞华1，李娜1，李伟2 日期：2009-11-16/span> 浏览：3160 查看PDF文档

基于神经网络算法的桥式起重机防摇摆控制*

丁瑞华1，李娜1，李伟2
(1.许昌学院 电气信息工程学院，河南 许昌 461000；2.郑州轻工业学院 机电工程学院，河南 郑州 450002)

摘要：针对桥式起重机运行过程中载荷摆动造成的运行精度差和工作效率低下问题，提出了一种神经网络直接逆模型控制方法，以降低载荷摆动。介绍了该控制系统中的神经网络逆模型控制器与辨识器的结构和算法；采用了带动量因子的BP算法调整权值，提高了神经网络学习速度；最后，应用Matlab对所设计系统进行了仿真测试。仿真实验结果表明，在不同载荷、绳长情况下，相对于PID控制方法，该方法具有更好的控制性能和鲁棒性。
关键词：神经网络；逆模型控制；起重机；载荷摆动
中图分类号：TH215;TP183文献标识码：A文章编号：1001-4551(2009)10-0027-04

Antiswing control based on neural network algorithm for trolley crane
DING Ruihua1, LI Na1, LI Wei2
(1. College of Electric and Information Engineering, Xuchang University, Xuchang 461000, China;
2. College of Mechanical and Electrical Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)
Abstract: Aiming at the problems of poor precision and low operation efficiency due to the payload oscillation of trolley crane, the neural network direct inverse control method was proposed to minimize the sway angle of load. The structure and algorithm of neural network inverse model controller and identifier were introduced, and the momentum back propagation learning algorithm was adopted to tune the weight values which increased the learning speed of neural networks. The Matlab simulation results show that the designed system has good performance and robustness than PID control method as the different load mass and rope length.
Key words: neural network; inverse model control; trolley crane; payload oscillation
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