| 在线学习自适应模糊控制器在水轮机调节中的应用 |
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| 引用本文： | 王淑青,李朝晖,张子蓬. 在线学习自适应模糊控制器在水轮机调节中的应用[J]. 武汉大学学报(工学版), 2005, 38(4): 9-13 |
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| 作者姓名： | 王淑青 李朝晖 张子蓬 |
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| 作者单位： | 华中科技大学,湖北,武汉,430074 |
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| 摘 要： | 针对水轮发电机组系统具有时变非线性,传统的控制方法很难达到最优控制的特性,提出采用基于RBF神经网络和遗传算法的自适应模糊控制器来控制水轮发电机组运行.模糊控制器的比例因子、模糊推理规则和隶属函数由遗传算法在线寻优.由RBF神经网络进行被控对象的动态特性模型辨识,以评价模糊控制器控制性能.仿真实验表明,控制效果良好,特别在变工况和扰动情况下优于最优PID控制.
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| 关 键 词： | 水轮机 模糊控制 遗传算法 RBF神经网络 |
| 文章编号： | 1671-8844(2005)04-009-04 |
| 修稿时间： | 2005-03-15 |
Application of on-line adaptive fuzzy controller to hydraulic turbine system |
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| WANG Shu-qing,LI Zhao-hui,ZHANG Zi-peng. Application of on-line adaptive fuzzy controller to hydraulic turbine system[J]. Engineering Journal of Wuhan University, 2005, 38(4): 9-13 |
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| Authors: | WANG Shu-qing LI Zhao-hui ZHANG Zi-peng |
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| Abstract: | Considering the nonliner and much varying feather of hydraulic turbine system in operation, conventional hydraulic turbine PID governor cannot control effectively; a new self-tuning fuzzy governor based on RBF neural networks and genetic algorithms is designed. The parameters and rules of fuzzy controller are optimized based on GA in operating. Dynamic identification model of hydraulic turbine system is designed based on the RBF neural networks to appraise the controlling performance of fuzzy controller. Simulation results show that the adaptive fuzzy controller is better than the traditional PID control strategy. |
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| Keywords: | hydraulic turbine fuzzy control genetic algorithms RBF neural networks |
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