Resource Allocation Network based Neural PID Adaptive Control for Generator Excitation System

摘要：

　　In this paper,a neural PID adaptive controller based on the identification of resource allocation network (RAN) was proposed for the generator excitation system,which not only has the ability of neural network such as powerful nonlinear mapping and self-learning,but also can adjust the PID controller performance.The controller dynamically increases the number of hidden nodes through the learning samples,building the model online and dynamically adjusting the PID parameters to achieve the system output tracking input.Simulation results show that this method is better to stabilize the static and dynamic terminal voltages of the generator compared to the conventional PID control.

关键词： Synchronous generator excitation system neural PID control resource allocation network

作者: Tengfei Zhang Jing Yang Fumin Ma

作者单位: College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China 2 College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, C

会议类型: 国际会议

会议名称: the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)

会议地点: 贵阳

会议语种:英文

页码: 1352-1357

在线出版日期: 2013-05-01（万方平台首次上网日期，不代表论文的发表时间）