液压机械补偿功率回收模型参考模糊神经网络控制  

Model Reference Fuzzy Neural Network Control of Hydraulic Mechanical Compensation Power Recovery

作　　者：谢光辉[1] 喇凯英[2] 王留运[2] 

机构地区：[1]北京工业职业技术学院,北京100042 [2]郑州大学机械学院,河南郑州450001

出　　处：《机床与液压》2009年第2期114-116,155,共4页Machine Tool & Hydraulics

摘　　要：介绍了液压系统试验中机械补偿功率回收的原理,建立了压力系统的数学模型。针对机械补偿功率回收系统影响压力的非线性因素多且多为缓变的特点,为满足试验要求提出了采用模型参考的模糊神经网络,提出了该网络实现的形式,设计了模糊神经网络和误差的逼近算法,根据要求确定了参考模型等。仿真结果表明:该控制方法能有效地跟踪参考模型,改变对象参数及负载输出压力无变化,能很好地满足试验要求。The theory of power recovery with mechanical compensation in hydraulic system test was introduced. The mechanical model of hydraulic pressure was established. According to the characteristics of mechanical compensation power recovery pressure sys- tem which has many nonlinear elements and changes slowly, model reference fuzzy neural networks was employed to satisfy the demand of experiment. The form of realizing the network was put forward, fuzzy neural network and approximate algorithm were designed. Reference model were designed according to the demand of experiment. Simulation results show that this control method can track ref- erence model efficiently. When changing the object parameter and load, the output pressure is not changed, it shows that this control method can satisfy the demand of experiment.

关 键 词：压力控制 功率回收 模型参考模糊神经网络 自适应控制 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]