👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆下载资源链接👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆
《《《《《《《《更多资源还请持续关注本专栏》》》》》》》
论文与完整源程序_电网论文源程序的博客-CSDN博客
https://blog.csdn.net/liang674027206/category_12531414.html
电网论文源程序-CSDN博客电网论文源程序擅长文章解读,论文与完整源程序,等方面的知识,电网论文源程序关注python,机器学习,计算机视觉,深度学习,神经网络,数据挖掘领域.https://blog.csdn.net/LIANG674027206?type=download
SCI《 A Neural-Network-Based Model Predictive Control of Three-Phase Inverter With an Output LC Filter》
模型预测控制(MPC)已成为一种成熟的现代控制方法。带输出LC滤波器的三相逆变器的ods，其中高质量的电压具有低总谐波需要失真(THD)。虽然它是一个直观的控制器，易于理解和实现，但它具有需要大量在线计算才能解决优化问题的显著缺点有问题。另一方面，无模型方法的应用，如基于人工神经的方法目前，网络方法在电力电子和驱动领域发展迅速。这篇论文提出了一种新的基于预测控制和前馈神经网络相结合的两电平变流器控制方案。以降低THD和提高系统的稳态和动态性能为目标不同类型的载荷。首先，在培训阶段使用MPC作为专家，以生成所需的数据对所提出的神经网络进行训练。然后，一旦对神经网络进行微调，它就可以成功在线用于电压跟踪目的，不需要使用MPC。
部分代码展示：
%%# This script calls all acquired data by MPC and combines them into the proper form
% for performing the training of the neural network, considering "Linear and Non-Linear" loads.clc; close all; clear;Input_8_Features = 1; % A logical parameter to choose/call the input features with a lenght of 9.
Input_8_Features_withOneDelay = 0; % A logical parameter to choose/call the input features with a lenght of 17.
Input_8_Features_with2Delays = 0; % A logical parameter to choose/call the input features with a lenght of 25.
LinearLoad = 0;%% Load the Data Files.
if LinearLoad == 0% Case #1: Linear Loads Samples = 60;
else% Case #2: Non-Linear Loads Samples = 70;
end
% To store the dataset
InputFeaturesSamples = cell(1, Samples);
TargetsSamples = cell(1, Samples);% Choose the kind of datatset for training the proposed neural network.
for i = 1:Samples% Calling the input vector with 9 features (including Ts intervals) and their corresponding targets. if Input_8_Featuresmyfilename = sprintf('Dataset/InputFeatures/Input_8Features/Sample%d.mat', i);myfilename1 = sprintf('Dataset/InputFeatures/Targets/Targets-8inputs/TargetSample%d.mat', i);% Calling the input vector with 17 features (including one-step delay of the eight features, and also Ts intervals)% and their corresponding targets. elseif Input_8_Features_withOneDelaymyfilename = sprintf('Dataset/InputFeatures/Input_8FeaturesWithDelay/OneDelaySamples/Sample%d.mat', i);myfilename1 = sprintf('Dataset/InputFeatures/Targets/TargetSample%d.mat', i);% Calling the input vector with 25 features (including two-steps delay of the eight features, and also Ts intervals)% and their corresponding targets. elseif Input_8_Features_with2Delaysmyfilename = sprintf('Dataset/InputFeatures/Input_8FeaturesWithDelay/TwoDelaysSamples/Sample%d.mat', i);myfilename1 = sprintf('Dataset/InputFeatures/Targets/TargetSample%d.mat', i);endInputFeaturesSamples{i} = importdata(myfilename); TargetsSamples{i} = importdata(myfilename1);
end% From cell to matrix conversion, the proper form for NN training.
T = cell2mat(TargetsSamples);
X = cell2mat(InputFeaturesSamples);
% neglect the last row, which contains the sampling time (i.e., Ts) intervals.
X = X((1:size(X,1)-1),:);
% nnstart效果展示：
194号资源-源程序：SCI文档+程序具有输出LC滤波器的三相逆变器的前馈神经网络模型预测控制-本人博客有解读资源-CSDN文库https://download.csdn.net/download/LIANG674027206/89795596👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆下载资源链接👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆👆
《《《《《《《《更多资源还请持续关注本专栏》》》》》》》
论文与完整源程序_电网论文源程序的博客-CSDN博客https://blog.csdn.net/liang674027206/category_12531414.html
电网论文源程序-CSDN博客电网论文源程序擅长文章解读,论文与完整源程序,等方面的知识,电网论文源程序关注python,机器学习,计算机视觉,深度学习,神经网络,数据挖掘领域.https://blog.csdn.net/LIANG674027206?type=download