| 基于递归神经网络的多变量系统预测控制 |
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| 引用本文： | 张燕,王繁珍,陈增强,袁著祉.基于递归神经网络的多变量系统预测控制[J].南开大学学报,2006,39(1):49-53,61. |
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| 作者姓名： | 张燕 王繁珍 陈增强 袁著祉 |
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| 作者单位： | [1]河北工业大学自动化系,天津300130 [2]南开大学自动化系,天津300071 |
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| 基金项目： | 中国科学院资助项目;科技部专项基金;南开大学校科研和教改项目 |
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| 摘 要： | 针对线性PID控制器系数难以整定的问题，构造了一种用神经网络实现的非线性PID控制器．多个具有相同结构的非线性PID控制器并联，对多变量系统实现解耦控制器．结合预测控制的思想，提出两种控制方案．第一种是在递归多步预测的基础上，在广义最小方差目标函数下实现控制，第二种利用多步预测目标函数在线修正解耦控制器的权值．仿真实验表明这两种方法的有效性．
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| 关 键 词： | 预测控制 解耦控制 递归神经网络 非线性PID控制 |
| 文章编号： | 0465-7942（2006）01-0049-05 |
| 收稿时间： | 2003-12-03 |
| 修稿时间： | 2003-12-03 |
Recurrent Neural Networks-based Multivariable System Predictive Control |
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| Zhang Yan,Wang Fanzhen,Chen Zengqiang,Yuan Zhuzhi.Recurrent Neural Networks-based Multivariable System Predictive Control[J].Acta Scientiarum Naturalium University Nankaiensis,2006,39(1):49-53,61. |
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| Authors: | Zhang Yan Wang Fanzhen Chen Zengqiang Yuan Zhuzhi |
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| Institution: | 1. Department of Automation, Hebei University of Technology, Tianjin 300130, China; 2. Department of Automation, Nankai University, Tianjin 300071, China |
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| Abstract: | A nonlinear PID controller is proposed based on recurrent neural network, due to the difficulty of tuning the parameters of conventional PID controller. In the control process of nonlinear multivariable system, a decoupling controller is constructed, which takes advantage of multi-nonlinear PID controllers in parallel. Under the idea of predictive control, two multivariable predictive control strategies are established. One is that the general minimum variance control function is used based on recursive multi-step predictive method. The other is that the multi-step predictive cost energy is adopted to train the weights of the decoupling controller, Simulation studies have shown their efficiency. |
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| Keywords: | predictive control decoupling control recurrent neural networks nonlinear PID control |
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