| 基于遗传神经网络的自适应PID控制器的设计 |
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| 引用本文： | 高志安,李良光,樊瑶.基于遗传神经网络的自适应PID控制器的设计[J].计算机工程与应用,2008,44(24):100-102. |
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| 作者姓名： | 高志安 李良光 樊瑶 |
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| 作者单位： | 安徽理工大学电气与信息工程学院,安徽,淮南,232001 |
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| 摘 要： | 提出了一种基于遗传算法和神经网络的自适应PID控制器的设计方法。该控制器主要由三个部分组成:利用遗传算法优化PID参数,和RBF神经网络结合,对被控对象逼近,搜索出一组准优的初始参数;RBF神经网络完成对被控对象Jacobian信息辨识;基于单神经元的自适应PID控制器,在线调整PID参数,以确保系统的响应具有最优的动态和稳态性能。仿真结果表明,控制器具有响应速度快,稳态精度高等特点,可用于控制不同的对象和过程。
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| 关 键 词： | 遗传算法 神经网络 自适应 神经元PID |
| 收稿时间： | 2007-10-23 |
| 修稿时间： | 2008-1-17
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Design of self-adaptive PID controller based on genetic neural networks |
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| GAO Zhi-an,LI Liang-guang,FAN Fan.Design of self-adaptive PID controller based on genetic neural networks[J].Computer Engineering and Applications,2008,44(24):100-102. |
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| Authors: | GAO Zhi-an LI Liang-guang FAN Fan |
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| Affiliation: | College of Electric Engineering，Anhui University of Science and Technology，Huainan，Anhui 232001，China |
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| Abstract: | A self-adaptive PID controller based on genetic algorithm and neural networks is presented.It consists of three parts: PID parameters are optimized by the genetic algorithm,and genetic algorithm combined with the RBF neural networks approaches the controlled object,searching for a group of initial parameters;RBF neural networks get Jacobian information;A self-adaptive PID controller based on the single neural network adjusts the PID parameters on line to insure the optimal dynamic and steady response.The simulation results show that the controller has a fast response speed,high steady precision.It can be used in different objects and processes. |
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| Keywords: | genetic algorithm neural networks self-adaptive neuron PID |
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