基于DRNN网络的凿岩钻臂自整定PID控制  

Self-setting PID control of rock drilling arms based on DRNN

作　　者：杜福银[1] 

机构地区：[1]西华大学机械工程与自动化学院,四川成都610039

出　　处：《矿山机械》2011年第4期14-17,共4页Mining & Processing Equipment

摘　　要：凿岩钻臂的自动定位系统是一个耦合的2输入2输出系统,系统存在响应较慢,负荷随机变化及参数快时变的特性。固定参数PID控制难以适应系统控制要求,因此,提出一种基于回归神经网络(DRNN)的2输入2输出PID控制器结构,给出了DRNN神经网络参数学习算法和PID控制器参数自整定算法。计算机仿真结果验证了该控制策略的可行性。The automatic positioning system for the rock drilling arm is a coupling system with two inputs and two outputs,and it has the features of slow response and loadings stochastic variation and rapid time-varying.Fixed-parametered PID control is hard to adapt to the controlling requirements of the system,so a kind of PID controller is proposed,which is constituted based on diagonal recurrent neural network （DRNN） with two inputs and two outputs.In addition,the learning algorithm of the parameters of DRNN and the self-setting algorithm of PID controller are offered.Finally,the feasibility of the proposed control strategy is verified via computer simulations.

关 键 词：凿岩钻臂 PID控制 回归神经网络(DRNN) 计算机仿真 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]