| 引用本文: | 王耀南 ，彭建春， 王 辉.基于高斯基神经网络的自学习控制及应用*[J].控制理论与应用,1998,15(5):701~707.[点击复制] |
| WANG Yaonan， PENG Jianchun and WANG Hui.Self-Learning Control Using Gaussian Potential FunctionNeural Networks and Its Application[J].Control Theory and Technology,1998,15(5):701~707.[点击复制] |
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| 基于高斯基神经网络的自学习控制及应用* |
| Self-Learning Control Using Gaussian Potential FunctionNeural Networks and Its Application |
| 摘要点击 923 全文点击 468 投稿时间：1995-11-09 修订日期：1997-10-31 |
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| DOI编号 |
| 1998,15(5):701-707 |
| 中文关键词 神经网络 学习算法 智能控制 收敛性分析 |
| 英文关键词 neural networks learning algorithm intelligent control |
| 基金项目 |
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| 中文摘要 |
| 本文提出一类基于高斯基神经网络的自学习控制器，该控制器由两个GPFN网络组成，一个完成PID学习控制，另一个完成未知被控对象模型的建模. 为加快网络的学习过程，文中提出了递归最小二乘法(RLS)用于神经网络的学习，并分析研究了自学习控制系统的收敛性和稳定性. 仿真和实验结果表明，这类智能控制是成功的. |
| 英文摘要 |
| This paper presents a new self-learning controller based on Gaussian potential function neural networks. The controller consists of a control network and model network. In order to speed up learning rate. a general least squares approach for neural network learning is proposed. Convergence and stability of this self-learning system is proved. Simulation results have shown that the new controller can be successfully ap-plied in nonliner control systems. |