| 粗糙-神经网络逆模补偿的发电机励磁复合控制 |
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| 引用本文： | 张腾飞,马福民.粗糙-神经网络逆模补偿的发电机励磁复合控制[J].电机与控制学报,2009,13(1). |
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| 作者姓名： | 张腾飞 马福民 |
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| 作者单位： | 1. 南京邮电大学,自动化学院,江苏,南京,210046
2. 南京财经大学,信息工程学院,江苏,南京,210046 |
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| 基金项目： | 江苏省教育厅高校自然科学基金基础研究项目，南京邮电大学引进人才科研基金 |
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| 摘 要： | 利用粗糙集数据智能分析与决策规则自动提取的优点以及神经网络良好的泛化能力,提出了粗糙-神经网络逆模型的具体实现方法;在证明五阶同步发电机模型可逆的基础上,研究了船舶同步发电机的粗糙-神经网络逆模型,提出了基于粗糙-神经网络逆模型前馈补偿的船舶发电机励磁复合控制方法,并对复合控制的稳定性和可靠性进行了分析.在某船舶电力仿真系统中进行了多工况仿真研究并进行了对比分析.仿真结果表明,粗糙-神经网络逆模型前馈补偿的复合控制可以提高船舶电力系统电压控制的稳态精确度、改善系统的动态性能.
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| 关 键 词： | 发电机 励磁控制 前馈补偿 复合控制 粗糙集 神经网络 |
Generator excitation compound control with rough neural network inverse system compensation |
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| ZHANG Teng-fei,MA Fu-min.Generator excitation compound control with rough neural network inverse system compensation[J].Electric Machines and Control,2009,13(1). |
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| Authors: | ZHANG Teng-fei MA Fu-min |
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| Affiliation: | 1.College of Automation;Nanjing University of Posts and Telecommunications;Nanjing 210046;China;2.School of Information Engineering;Nanjing University of Finance & Economics;China |
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| Abstract: | The integration of rough set with neural network comprehensively can utilize the merits of rough set,such as data intelligent analysis and automatic extraction of decision-making rules,and the ability of arbitrarily approximating nonlinear functions in neural network.The concept of rough neural network inverse model was first put forward and the realization method was introduced.After proving the reversibility of the fifth-order generator model,the rough neural network inverse model for ship synchronous gen... |
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| Keywords: | generators excitation control feed forward compensation compound control rough set neural network |
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