SINGLE NEURON PID MODEL REFERENCE ADAPTIVE CONTROL BASED ON RBF NEURAL NETWORK

摘要：

Radial Basis Function (RBF) neural network (NN) is powerful computational tools,which have been used extensively in the areas of pattern recognition, systems modeling and identification due to the advantages of simple construction, adaptability and robustness. This paper presents a novel approach of single neuron PID model reference adaptive control (MRAC) control based on RBF neural network on-line identification. A RBF network is built to identify the system on-line, and then it constructs the on-line reference model, implements self-learning of controller parameters by single neuron controller, and thus achieves on-line regulation of controllers parameters. The simulation result shows that the proposed method can construct processing model through on-line identification and then give gradient information to neuron controller, it can achieve on-line identification and on-line control with high control accuracy and good dynamic performance.

关键词： RBF neural network single neuron PID model reference adaptive control (MRAC) simulation

作者: MING-GUANG ZHANG WEN-HUI LI

作者单位: School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou,730050, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3021-3025

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）