摘要
针对利用Wiener模型表达的具有动态非线性的传感器进行系统辨识和性能补偿。将系统分解为动态非线性环节和静态线性环节,利用函数链人工神经网络和遗传算法分别进行系统辨识,通过静态非线性补偿将系统简化为线性系统,再进行动态性能补偿。利用LabVIEW设计虚拟仪器,经过仿真表明该方法是有效的。
The sensors which can be described by Wiener model and have nonlinear dynamic characteristic are identified as well as compensated. The system is expressed by a linear dynamic subunit followed by a nonlinear static one. The two subunits are identified using functional link artificial neural network and genetic algorithm respectively. The dynamic compensation is carried out after the system is simplified to a linear one through the nonlinear static compensation, Effectiveness of this method is tested by a simulation based on virtual instrument designed with LabVIEW,
出处
《微计算机信息》
北大核心
2006年第03S期189-191,共3页
Control & Automation
关键词
系统辨识
函数链人工神经网络
遗传算法
动态补偿
system identification
functional link artificial neural network
genetic algorithm
dynamic compensation