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Update GA_PID.m

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TianZhendong 6 years ago
committed by GitHub
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bda469003c
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  1. 58
      GA_PID.m

58
GA_PID.m

@ -2,21 +2,19 @@
clc;
clear;
close all;
%% 参数设置
ChromosomeSize = 3; %染色体长度,参数的个数,PID有三个参数
PopulationSize = 100; %种群规模
MaxIter = 100; %最大迭代次数
% MinFitness=0.01; %最小适应值 这里PID适应度函数取的倒数,因此应为最大。
MinFitness=0.01; %最小适应值
% CrossRate=0.6; %交叉概率
MutateRate=0.2; %变异概率
NoChangeNo=5; %直接复制的父辈的染色体数量
UpLimit=30; %基因上限
%% 全局变量 pid的三个参数
ObjFun=@PSO_PID; %适应值函数
NoChangeNo=5;
UpLimit=30; %上限
global Kp;
global Ki;
global Kd;
%% 初始化种群init.m
Population=rand(PopulationSize,ChromosomeSize); %种群,预分配内存
for i=1:PopulationSize
@ -36,18 +34,18 @@ AveFitness=zeros(MaxIter,1);
Elite=zeros(MaxIter,ChromosomeSize); %用于记录每一代的最优解
for Iter=1:MaxIter
disp(['迭代次数:',num2str(Iter)]);
% 适应值计算Fitness
disp(['迭代次数:',num2str(Iter)]); %显示迭代进度
%% 适应值计算Fitness
for i=1:PopulationSize
Kp=Population(i,1);
Ki=Population(i,2);
Kd=Population(i,3);
PopulationFitness(i,:) = fitness(Kp,Ki,Kd);
PopulationFitness(i,1) = fitness(Kp,Ki,Kd);
end
% 适应值大小排序,并保存最佳
%% 适应值大小排序,并保存最佳个体和最佳适应度
FitnessSum=sum(PopulationFitness); %种群累加适应度
AveFitness(Iter,1)=FitnessSum/PopulationSize;
AveFitness(Iter,1)=FitnessSum/PopulationSize; %种群平均适应度
[PopulationFitness,Index]=sort(PopulationFitness); %适应值从小到大排序
BestFitness(Iter,1) = PopulationFitness(MaxIter,1); %最佳适应度
Elite(Iter,:) = Population(Index(MaxIter),:); %记录本代的精英
@ -73,7 +71,7 @@ for Iter=1:MaxIter
r1=rand*FitnessSum;
for k=1:PopulationSize
m1=m1+PopulationFitness(k);
if r1<m1
if r1<=m1
idx1=Index(k);
break;
end
@ -83,7 +81,7 @@ for Iter=1:MaxIter
r2=rand*FitnessSum;
for k=1:PopulationSize
m2=m2+PopulationFitness(k);
if r2<m2
if r2<=m2
idx2=Index(k);
break;
end
@ -131,6 +129,33 @@ for Iter=1:MaxIter
clear last;
clear idx;
clear mid;
% clear PopulationNew;
%交叉操作 crossover
% for i=1:PopulationSize
% % rand<交叉概率,对两个个体的染色体串进行交叉操作
% if(rand < CrossRate)
% acr_position = floor(ChromosomeSize*rand+1); %要交叉的节点
% % if (cross_position == 0 || cross_position == 1)
% % continue;
% % end
% acr_chrom = floor((PopulationSize-1)*rand+1); %要交叉的染色体,floor取比它小的整数,acr_chrom取值在1-N
% for j=1:acr_position
% temp = Population(i,j);
% Population(i,j) = Population(acr_chrom,j);
% Population(acr_chrom,j) = temp;
% end
%
% end
% end
% clear i;
% % clear j;
% clear temp;
% clear acr_chrom;
clear i;
clear j;
@ -138,6 +163,7 @@ for Iter=1:MaxIter
K_i(1,Iter)=Elite(Iter,2);
K_d(1,Iter)=Elite(Iter,3);
end
figure(1)
plot(BestFitness,'LineWidth',2);
@ -146,3 +172,9 @@ plot(K_p)
hold on
plot(K_i,'k','LineWidth',3)
plot(K_d,'--r')

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