| 基于神经网络的非线性预测函数控制 |
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| 引用本文： | 张泉灵 王树青. 基于神经网络的非线性预测函数控制[J]. 浙江大学学报(工学版), 2001, 35(5): 497-501 |
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| 作者姓名： | 张泉灵 王树青 |
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| 作者单位： | 张泉灵（浙江大学,工业控制技术国家重点实验室,浙江,杭州,310027） 王树青（浙江大学,工业控制技术国家重点实验室,浙江,杭州,310027） |
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| 基金项目： | 浙江省科委重点资助项目(991101131). |
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| 摘 要： | 给出了一种新的神经网络多步预估器结构，建立了CSTR过程的人工神经元网络的动态模型，并在此基础上提出了基于人工神经元网络模型的非线性预测函数控制算法．给出了非线性预测函数控制的具体实施步骤．计算机仿真表明。人工神经元网络模型的精度已满足预测控制的需要。该控制系统比常规PID控制器具有更好的控制效果．
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| 关 键 词： | 人工神经元网络 非线性 预测函数控制 模型预测控制 连续带搅拌反应器 |
| 文章编号： | 1008-973X(2001)05-0497-05 |
| 修稿时间： | 1999-12-21 |
Nonlinear predictive functional control based on a neural network |
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| ZHANG Quan-ling,WANG Shu-qing,. Nonlinear predictive functional control based on a neural network[J]. Journal of Zhejiang University(Engineering Science), 2001, 35(5): 497-501 |
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| Authors: | ZHANG Quan-ling WANG Shu-qing |
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| Abstract: | An Artificial Neural Network (ANN) is an adequate tool for modeling nonlinear systems and can be applied straightforward in the predictive functional control which belongs to the classical family of model predictive control. New structure of ANN multi-step prediction that is different from cascade or parallel is given, at the same time, the nonlinear predictive functional control using the ANN model is developed for control of high-nonlinear system. The performance of this strategy is evaluated by applying it to a Continuous Stirred Tank Reactor(CSTR). The results illustrate that the NPFC using ANN model is more effective for control nonlinear system than PID control. |
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| Keywords: | artificial neural network nonlinear predictive functional control model based predictive control continuous stirred tank reactor (CSTR) |
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