| 基于模糊神经网络的参数自整定PID控制系统设计 |
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| 引用本文： | 刘文军,牛昱光.基于模糊神经网络的参数自整定PID控制系统设计[J].太原理工大学学报,2006,37(3):298-301,305. |
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| 作者姓名： | 刘文军 牛昱光 |
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| 作者单位： | 太原理工大学,信息工程学院,山西,太原,030024 |
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| 摘 要： | 利用多层神经网络构建模糊自适应PID控制器，通过神经网络自学习能力在线提取模糊控制规则，优化控制器隶属度函数，根据不同时刻的误差e和误差变化ec运用模糊推理在线自整定PID参数。仿真实验表明，该控制系统具有优良的控制性能。此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
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| 关 键 词： | 模糊神经 自适应PID 遗传算法 建模 仿真 |
| 文章编号： | 1007-9432（2006）03-0298-04 |
| 收稿时间： | 2005-10-24 |
| 修稿时间： | 2005-10-24 |
Control System Design Of Self-tuning PID-Type Based On Fuzzy Neural Network |
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| LIU Wen-jun,NIU Yu-guang.Control System Design Of Self-tuning PID-Type Based On Fuzzy Neural Network[J].Journal of Taiyuan University of Technology,2006,37(3):298-301,305. |
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| Authors: | LIU Wen-jun NIU Yu-guang |
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| Institution: | College of Information Engineering of TUT , Taiyuan 030024 ,China |
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| Abstract: | This paper utilizes multilayer neual network to construct a fuzzy self-tuning PID controller.The controller can get hold of fuzzy rules and optimize its subjection function online by self-learning ability of the neual network,and it also can adjust PID parameter in operation according to "e" and "ec "at different time by fuzzy reasoning.The excellent control performance of the control system is proved by computer Simulation.In addition,The paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network,which can ensure that the controller achieves optimization control. |
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| Keywords: | Fuzzy-Neural self-tuning PID genetic algorithms modeling simulation |
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