神经网络逆控制在矿井提升机调速系统中的仿真研究  

Simulation of Neural Network Inverse Control in Mine Hoist Speed System

作　　者：王颖[1] 

机构地区：[1]黑龙江工业学院电气与信息工程系,黑龙江鸡西158100

出　　处：《数字技术与应用》2016年第2期5-6,共2页Digital Technology & Application

摘　　要：利用神经网络能够逼近任意非线性的能力,将其与非线性逆系统相结合,对矿井提升机调速控制系统的逆模型进行建模,提出了一种新的控制策略。该策略以逆系统理论为依据,将矿井提升机调速控制系统作为被控对象,采用积分器与静态的多层前馈神经网络相结合的方式,搭建动态神经网络结构,用来逼近其逆系统,同时结合经典控制方法,设计出调速系统的PID-神经网络逆控制器。仿真结果表明:所设计的系统能够实现对矿井提升机调速的有效控制,具有响应速度快、跟踪能力强的优点。Using neural network to the ability to approximate any nonlinear, the and nonlinear inverse system combination, of mine hoist speed control system of the inverse model of the modeling, a new control strategy is proposed. The strategy to inverse system theory as the basis, the mine lifting machine speed control system as the object, the integrator and static multi-layer feedforward neural network combination way, build dynamic neural network structure, used to approximate the inverse system, combined with the classical control method, the design of the speed control system of PID neural network inverse controller. The simulation results show that the designed system can realize the effective control of engine speed control of mine hoist. A response has the advantages of fast speed, strong tracking ability.

关 键 词：矿井提升机 神经网络 逆系统 神经网络逆控制器 

分 类 号：TM921.5[电气工程—电力电子与电力传动]