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对具有随机噪声的二阶系统的模型辨识
- matlab在系统辨识中的应用此处为对具有随机噪声的二阶系统的应用的源代码及运行后结果（包括图像）-Matlab system identification in the application is right here for the second random noise of the system source code and running after the results (including images)
对具有随机噪声的二阶系统的模型辨识
- matlab在系统辨识中的应用此处为对具有随机噪声的二阶系统的应用的源代码及运行后结果（包括图像）-Matlab system identification in the application is right here for the second random noise of the system source code and running after the results (including images)
ghmm470
- 对具有随机噪声的二阶系统的模型辨识，进行标幺化以后系统的参考模型差分方程为： y(k)=a1*y(k-1)+a2*y(k-2)+b*u(k-1)+s(k) 式中，a1=0.3366,a2=0.6634,b=0.68,s(k)为随机噪声。由于神经网络的输出最大为1，所以，被辨识的系统应先标幺化，这里标幺化系数为5。采用正向建模(并联辨识)结构，神经网络选用3-9-9-1型，即输入层i，隐层j包括2级，输出层k的节点个数分别为3、9、9、1
ch3ch4ch6辨识程序夹
- 系统辨识是控制的前提，获得较为准确地模型才能对系统进行进一步的控制。此为《系统辨识及其MATLAB仿真〉一书中所附的程序-control system identification is the prerequisite for access to more accurate model of the system can be further controlled. As the "System Identification
系统辨识源码
- 系统辨识与参数估计源代码。可以对一个未知模型做出估计。-system identification and parameter estimation source code. Can a model to estimate the unknown.
mbp
- 对具有随机噪声的二阶系统的模型辨识(用改进的神经网络MBP算法辨识)-of random noise with the second-order system model (used to improve the neural network algorithm for identification MBP)
xitongbianshi
- 这是一个用系统模型辨识用的PSO程序,它主要是用于系统的参数未知时,此时比较方便.-This is a used system model identification procedures used in PSO, it is mainly used for systems with unknown parameters, the more convenient at this time.
m12_5
- 神经网络模型辨识及其MATLAB实现范例-Neural network model identification and implementation examples of MATLAB
subspace-methods
- 本文介绍了子空间模型辨识的多种方法，并对其不同的方法进行了综合的分析，研究，比较。-This paper introduces the sub-space model identification of a number of ways, and different ways to carry out a comprehensive analysis, research, compare.
bianshi2
- 一个复杂系统神经网络辨识,采用改进BP算法对随机噪声的二阶系统进行模型辨识,效果挺好的.-A complex neural network system identification, using BP algorithm to improve the random noise of the second-order system identification model, the effect of the good.
ModelIdentification
- 关于模型辨识的MATLAB仿真源码。有使用最小二乘的建模，有极大似然估计建模的方法。每个重点例句都有详细的解释。-On the MATLAB simulation model of source identification. Modeling the use of least squares, and maximum likelihood estimation method of modeling. Each key has a de
systemidentify
- 系统辨识源码，包含参数模型辨识算法程序和非参数模型辨识算法程序。-Source system identification, model identification algorithm contains parameters of procedures and non-parametric procedures for model identification algorithm.
trn_2in
- 模型辨识 模糊神经网络 T-S模型 输入输出 前提参数 结论参数-Model Identification of TS Fuzzy Neural Network model input and output parameters of the premise parameters Conclusion
xijun
- 本文提出了一种新的基于细菌生存优化(Bacterial Foraging Optimization –BFO)的非线性模型辨识方法。它是利用群集智能仿生BFO算法对一类Hammerstein系统进行辨识，从而估计出它的参数模型-This paper presents a new optimization based on bacterial survival (Bacterial Foraging Optimization-BFO) n
FuzzyMpc
- 模糊T-S预测控制的matlab代码，实现基于模糊模型辨识的广义预测控制-TS fuzzy matlab code predictive control, fuzzy model identification-based generalized predictive control
batterytest
- 锂电池模型动力锂电池RC等效模型辨识方法双RC模型的搭建(Lithium battery model, power lithium battery, RC equivalent model identification method, double RC model)
主要程序
- 粒子群算法的仿真程序，并采用典型benchmark进行演示分析； 然后，应用粒子群算法进行热工过程水轮机系统模型辨识，matlab软件可直接运行； 采用粒子群算法与PID参数整定进行联合仿真，用以提高PID控制器对热工过程水轮机的控制性能。(Particle swarm algorithm simulation program, and the use of a typical benchmark for demonstration
DH
- 带有死区的hammerstein模型辨识(Identification of Hammerstein model with dead time)
电池1阶RC模型辨识数据及程序
- 一阶rc电路的电池1阶RC模型辨识数据及程序(Identification Data and Procedures of First Rc Circuit Battery First Rc Model)
锂离子电池模型
- 可用于锂电池模型建立，利用最小二乘法进行参数辨识与仿真分析(Second order RC equivalent circuit model)