摘要
针对滞后慢时变系统,利用 Adaline 网络在线辨识被控对象的静态增益和纯滞后时间,实时调整 Smith 预估器的参数,并采用补偿模糊神经网络作为控制器的控制方法。将该方法用于纸浆浓度控制系统,仿真实验结果表明了该方法的有效性和实用性。
Considering time-varying delay systems, the static gain and time delay of these controlled objects are identified on-line by use of Adaline network and parameters of Smith predictor are adjusted in real-time, and a new controller with compensation fuzzy neural network is used in the method. The method is employed in the pulp consistency control system. Simulation results show that the method is efficient and practical.
出处
《电气自动化》
北大核心
2007年第3期3-5,28,共4页
Electrical Automation
基金
北京市教委科技发展计划项目
项目编号:km200611417007
