电动负载模拟器的非线性因素分析及补偿  

Analysis and compensation for the nonlinearity of electric load simulator

作　　者：付梦瑶 杨瑞峰[1,2] 郭晨霞[1,2] 张鹏[1,2] 张新华 

机构地区：[1]中北大学仪器与电子学院,山西太原030051 [2]中北大学仪器科学与动态测试教育部重点实验室,山西太原030051 [3]北京自动化控制设备研究所,北京100000

出　　处：《中国测试》2016年第1期96-101,共6页China Measurement & Test

基　　金：国家自然科学基金项目(51375462);国家国际科技合作项目(2014DFR70650)

摘　　要：为提高电动负载模拟器系统的动态性能和信号跟踪准确度,提出针对系统摩擦非线性和间隙非线性进行补偿的方法。分析系统存在的非线性因素及其对系统造成的影响,在此基础上建立其非线性数学模型。采用基于小波神经网络的PID控制器实现摩擦非线性补偿,同时利用间隙逆模型针对间隙非线性进行补偿。利用Matlab软件对补偿结果进行仿真验证,仿真结果显示经过补偿后系统正弦响应曲线跟随性能变好,跟踪误差明显减小,准确度得到很大改善。仿真结果证明:基于小波神经网络的PID控制器和间隙逆模型分别对摩擦非线性和间隙非线性有明显的抑制效果,系统动态性能得到提高。To improve the dynamic performance and signal tracking accuracy of electric load simulator systems, a method have been proposed for compensating the friction nonlinearity and the gap nonlinearity of the system. Particularly, the nonlinear factors of the system and its impact are analyzed and a nonlinear mathematical model has been established. The friction nonlinearity is compensated with a PID controller based on the wavelet neural network and the gap nonlinearity is compensated through a gap inverse model. The results are verified with MATLAB software. The simulation test shows that, after compensation, the tracing performance of the sinusoidal response curve of the system is improved and the tracking error is largely reduced. Also, the simulation results indicate that the PID controller and the gap inverse model have significantly inhibited friction nonlinearity and gap nonlinearity so as to enhance the dynamic performance of the system.

关 键 词：电动负载模拟器 非线性 摩擦补偿 神经网络 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]