| 基于改进的BP神经网络模型参考自适应控制 |
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| 引用本文： | 李红,杨剑锋.基于改进的BP神经网络模型参考自适应控制[J].兰州铁道学院学报,2011,30(1):37-41. |
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| 作者姓名： | 李红 杨剑锋 |
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| 作者单位： | 兰州交通大学,自动化与电气工程学院,甘肃,兰州,730070 |
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| 摘 要： | 针对传统BP算法的神经网络模型参考自适应控制实时性差、精度不高、收敛慢等不足,结合BP改进算法和非线性系统的可逆性,提出了基于改进的双向权值调整BP算法的神经网络模型参考自适应控制.基于此算法设计的系统辨识器和控制器的网络结构简单,精度高,仿真结果表明该算法的辨识和控制效果均很理想,可应用于工程实际.
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| 关 键 词： | 神经网络 改进的双向权值调整 自适应控制 |
Model Reference Adaptive Control Based On the Improved BP Neural Network |
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| LI Hong,YANG Jian-feng.Model Reference Adaptive Control Based On the Improved BP Neural Network[J].Journal of Lanzhou Railway University,2011,30(1):37-41. |
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| Authors: | LI Hong YANG Jian-feng |
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| Institution: | LI Hong,YANF Jian-feng(School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China) |
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| Abstract: | Because of some problems of the model reference adaptive control based on the traditional BP algorithm,such as the real-time performance,low precision,slow training and so on,and combining the improved BP algorithm and the reversibility of the nonlinear system,this paper proposes the model adaptive control based on the improved bi-phase weight adjusting algorithm to train neural networks.Using the proposed algorithm,the network structure of the system identification and controller is simple and precise.The ... |
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| Keywords: | neural network the improved bi-phase weight adjusting adaptive control |
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