基于模糊模型和神经网络的某扫雷犁系统建模  

Modelling of the Electrohydraulic Servo System of a Certain Mine Sweeping Plough Based on Fuzzy Model and Neural Network

作　　者：张媛[1] 邢宗义[1] 秦勇[2] 贾利民[2] 

机构地区：[1]南京理工大学机械工程学院,江苏南京210094 [2]北京交通大学交通运输学院,北京100044

出　　处：《计算机仿真》2010年第5期21-26,108,共7页Computer Simulation

摘　　要：在实现扫雷犁系统准确位置控制的研究中,由于扫雷犁电液伺服系统固有的流量-压力特性等非线性因素,采用传统机理建模方法难以获得其精确模型,研究了系统的两种智能建模方法,即模糊建模和神经网络建模。模糊建模方法采用基于GK聚类算法的TS模糊模型,神经网络建模中采用了基于正交最小二乘算法的径向基函数神经网络。通过对扫雷犁电液伺服系统进行的建模实验仿真,分析了两方法的建模性能并与其他建模方法进行了对比,研究结果验证了所提出两种建模方法的有效性。The mine sweeping plough is a certain type of electrohydraulic servo system with complex nonlinear characteristics including flow/pressure relation, etc, and it is difficult to construct its accurate model by first principle method. This presented study focused on modeling the system using two intelligent methods, i.e. fuzzy modeling and neural network modeling. TS fuzzy model based on GK clustering algorithm is adopted in fuzzy modeling and radial basis function （RBF） neural network based on orthogonal least square method is used in neural network modeling. The two proposed methods are applied to the electrohydraulic servo system, and the results show their validity compared with other modelling techniques.

关 键 词：电液伺服系统 建模 径向基函数神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TJ812[自动化与计算机技术—控制科学与工程]