摘要
镍电解三段净化工序中传感器检测信号种类复杂,现场物化条件差,提出应用机械手实现镍电解净化过程中检测的自动化。建立了机械手的广义运动模型和死区描述模型,在此基础上实现了径向基神经网络(Radial Basis Function Neural Networks,RBFNN)死区补偿控制器设计,系统有系统估计和死区补偿两个RBFNN实现,给出了系统估计和死区补偿自适应率设计。仿真结果显示,该系统能实现机械手的位置跟踪和死区补偿,提高镍电解的检测自动化水平。
The monitor device with manipulator was proposed based on three-segment purifying process in nickel electro winning which has complex sensors and bad physical-chemical conditions.The dynamic model of manipulator and dead zone was established;also compensate control with RBFNN strategy was applied to this repeat system,and the compensator was designed with dead zone compensation and system estimation,and the adaptive law was designed for this control system.The simulation shows RBFNN compensate control have good trajectory tracking ability and then the monitor automation of purifying process in nickel electro-winning realized.
出处
《机械设计与制造》
北大核心
2013年第3期208-210,共3页
Machinery Design & Manufacture
基金
河南省科技厅科技攻关计划资助项目(122102210416
112102210339)
关键词
机械手
死区
神经网络
自适应率
仿真
Robotic Manipulator
Dead-Zone
Neural Networks
Adaptive Law
Simulation
