| 基于RBF神经网络的电力系统自适应励磁控制器的设计 |
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| 引用本文： | 时海涛,李树荣.基于RBF神经网络的电力系统自适应励磁控制器的设计[J].中国石油大学学报(自然科学版),2003,27(6). |
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| 作者姓名： | 时海涛 李树荣 |
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| 作者单位： | 1. 石油大学信息与控制工程学院,山东东营,257061;中国科学院半导体研究所,北京,100083
2. 石油大学信息与控制工程学院,山东东营,257061 |
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| 基金项目： | 国家“973”资助项目 (T19980 2 0 3 0 0 ) |
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| 摘 要： | 采用后推设计算法设计了SISO严格反馈系统的RBF神经网络自适应控制器。权值的调整算法基于所选择的积分型的Lyapunov函数 ,能保证整个闭环系统是最终一致有界的。把所设计的控制方案用于电力系统的励磁控制中。仿真结果表明 ,所设计的控制器具有良好的跟踪性能和鲁棒性
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| 关 键 词： | 非线性自适应励磁控制器 径向基神经网络 后推算法 最终一致有界 鲁棒性 |
Design of adaptive excitation controller for a power system based on radial basis neural network |
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| SHI Hai-tao and LI Shu-rong. College of Information and Control Engineering in the University of Petroleum,China,Dongying.Design of adaptive excitation controller for a power system based on radial basis neural network[J].Journal of China University of Petroleum,2003,27(6). |
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| Authors: | SHI Hai-tao and LI Shu-rong College of Information and Control Engineering in the University of Petroleum China Dongying |
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| Institution: | SHI Hai-tao and LI Shu-rong. College of Information and Control Engineering in the University of Petroleum,China,Dongying 257061 |
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| Abstract: | An adaptive controller based on radial basis neural network of SISO strict-feedback system was designed by using back-stepping method. The tuning laws for weights of neural network were derived from an integral Lyapunov function which was newly selected. So the stability of the closed loop can be guaranteed. The proposed scheme has been applied to design of an excitation controller for a power system. The simulation shows the good tracking performances and robustness of the newly designed controller. |
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| Keywords: | nonlinear adaptive excitation controller radial basis neural network back-stepping calculation ultimately uniform boundary robustness |
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