自适应神经模糊推理系统在起重机稳钩控制中的应用-《郑州大学学报(工学版)》

文章信息/Info

Title:: Application of adaptive neural fuzzy reasoning system in crane hook control

作者:: 黄士涛; 胡全义; 马进元; 等.; 郑州大学,机械工程学院,河南省,郑州,450001, 郑州大学,机械工程学院,河南省,郑州,450001, 郑州大学,机械工程学院,河南省,郑州,450001, 郑州大学,机械工程学院,河南省,郑州,450001

Keywords:: adaptive neural fuzzy reasoning system; anti-sway control; Blended learning algorithms

摘要:: 起重机小车-吊重系统具有多变量、非线性和钢丝绳长度不确定性的特点,造成吊物移动过程中摇摆很难控制.提出一种基于自适应神经模糊推理系统(ANFIS)的控制方法应用于起重机的稳钩控制,该方法采用反向传播算法(BP)和最小二乘算法(LS)的混合算法对小车-吊重系统样本数据进行学习,调整各变量的隶属度函数,自动产生模糊规则.仿真结果表明,这种控制方法对小车-吊重系统的摇摆角度和小车位置的控制过程具有良好的动态性能和较强的鲁棒性能,说明了自适应神经模糊推理系统在起重机稳钧控制中的有效性.

Abstract:: The crane trolley-lifting system has the characteristics of multivariation, nonlinearity and uncertainty of wire rope length, which makes it difficult to control the rocking during the movement of the lifting object. A control method based on adaptive neural fuzzy reasoning system (ANFIS) is proposed to be applied to the stable hook control of cranes, which uses a hybrid algorithm of backpropagation algorithm (BP) and least squares algorithm (LS) to learn the sample data of the trolley-lifting system, adjust the membership function of each variable, and automatically generate fuzzy rules. The simulation results show that this control method has good dynamic performance and strong robustness for the control process of the rocking angle and trolley position of the trolley-lifting system, which shows the effectiveness of the adaptive neural fuzzy reasoning system in the crane steady control.