非线性系统建模

文档编号:DQ324   文档字数:10271,页数:28

 摘要
 非线性系统本身机理存有着复杂性，现在对解决非线性问题的方法还有很大的局限性。所以我们要对几种非线性系统建模的建模方法和他们的仿真效果进行进一步的比较，归纳出他们各自的优缺点，以便能更好，更灵活的适用在社会各个生产系统中。这里分析介绍了神经网络建模和多项式建模两种非线性系统建模的方法和仿真，并对他们进行了比较和分析。
神经网络模型有着精度高，误差小的特点。但是因为BP训练时，要求函数的梯度，运算量大，所以程序执行更加费时。而多项式系统建模存在着精度低，误差大的问题。在高要求的情况下尽量不要选择多项式系统建模。多项式系统建模运算速度快，训练时间短是多项式系统建模的最大优点。
 本文档以BP人工神经网络和多项式为数学工具，对非线性系统的建模方法进行讨论，并以无线通信中的射频功率放大器为例，展示了所研究的建模方法的应用。
 
 
关键词：非线性系统；BP神经网络；多项式模型
Abstract
 The nonlinear system itself mechanism is having the complexity, now to solves the non-linear problem method also to have the very big limitation. Therefore we must carry on the further comparison to several nonlinear system modelling method and their simulation effect, induces they respective good and bad points, in order to be better, more nimble being suitable in society each production system. Here analyzed introduced the neural network modelling and the multinomial modelling two nonlinear system modelling's method and the simulation, and have carried on the comparison and the analysis to them. the neural network model has the precision to be high, erroneous small characteristic. But when BP training, the request function's gradient, the operand is big, therefore the program execution is more time-consuming. But the multinomial system modeling has the precision to be low, erroneous major problem. Do not choose the multinomial system modeling as far as possible in the high request's situation. The multinomial system modeling operating speed is quick, the training time short is the multinomial system modeling biggest merit.
 Utilizes two nonlinear system modelling method in the radio frequency power amplifier to use under a procedure to carry on the deep level to them the comparison, looked that the output chart analyzes they respective good and bad points.
 
Keywords: Nonlinear system; BP neural network; Multinomial model
目录

1 前言 1
1.1 非线性系统建模的意义 1
1.2 非线性系统建模的方法 2
1.3 文档结构 2
2 非线性系统的BP神经网络模型 4
2.1 神经网络概论介绍 4
2.2 BP神经网络基本理论 6
2.3 BP神经网络仿真 10
3 非线性系统的多项式模型 14
3.1 多项式拟合基础 14
3.2 多项式模型的MATLAB实现方法 15
3.3 多项式拟合仿真 17
4 在射频功率放大器中的应用 19
4.1 无线通讯中的射频功率 19
4.2 射频功率的BP神经网络和多项式仿真及分析 19
5 总结 26
致谢 27
参考文献 28

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