mohureal.asv

氧乐果控制过程

% sga
%
% This script implements the Simple Genetic Algorithm described
% in the examples section of the GA Toolbox manual.
%

% Author:     Andrew Chipperfield
% History:    23-Mar-94     file created
clear all
close all
global rin yout timef ntt mtt nmtol kk ts u P a b et Tdelay x1 x2 AA;
NIND =50;           % Number of individuals per subpopulations
MAXGEN = 50;        % maximum Number of generations
GGAP = .9;           % Generation gap, how many new individuals are created
%%%%%%%%%%%%%%%%修正模型的参数及采样周期%%%%%%%%%%%%%%%
ts=10;          %采样周期
rin=1;
P=100;          %影响参数的变化速率
% Build field descriptor
FieldD1 = rep([-2;2],[1,12]);
FieldD2 = rep([-1;1],[1,1]);
% FieldD3 = rep([0;1],[1,5]);
FieldD1 = rep([0;1],[1,]);
FieldD2 = rep([-1;1],[1,1]);
% FieldD1 = rep([0;1],[1,7]);
% FieldD2 = rep([-1;1],[1,1]);
FieldD=[FieldD1 FieldD2];
% FieldD=[FieldD1 FieldD2 FieldD3];
A=[];
   Chrom = crtrp(NIND, FieldD);
% Chrom=rep([0.8 0.75 0.6 0.1 0.2 0.2],[NIND,1]);
% Reset counters
   Best = NaN*ones(MAXGEN,1);	% best in current population
   gen = 0;			% generational counter
% Evaluate initial population
   ObjV = mohupidobj(Chrom);
% Track best individual and display convergence
   Best(gen+1) = min(ObjV);
   plot(log10(Best),'r');xlabel('generation'); ylabel('log10(f(x))');
   text(0.5,0.95,['Best = ', num2str(Best(gen+1))],'Units','normalized');   
   drawnow;        
% Generational loop
   while gen < MAXGEN,
    % Assign fitness-value to entire population
       FitnV = ranking(ObjV);
    % Select individuals for breeding
       SelCh = select('sus', Chrom, FitnV, GGAP);
    % Recombine selected individuals (crossover)
       SelCh = recint(SelCh);
    % Perform mutation on offspring
       SelCh = recmut(SelCh,FieldD);
    % Evaluate offspring, call objective function
       ObjVSel = mohupidobj(SelCh);
    % Reinsert offspring into current population
       [Chrom ObjV]=reins(Chrom,SelCh,1,1,ObjV,ObjVSel);
    % Increment generational counter
       gen = gen+1;
    % Update display and record current best individual
       Best(gen+1) = min(ObjV);
       plot(log10(Best),'r'); xlabel('generation'); ylabel('log10(f(x))');
       text(0.5,0.95,['Best = ', num2str(Best(gen+1))],'Units','normalized');
       drawnow;
       
     [OderJi,IndexJi]=sort(ObjV);
       BestJ=IndexJi(1);
       AA=[AA; Chrom(BestJ,:)]

   end 
   
[OderJi,IndexJi]=sort(ObjV);
BestJ=IndexJi(1);
A=Chrom(BestJ,:)
% yaa=[];
% for i=1:100
%     a=mohupidobj(AA(i,:))
%     yaa=[yaa;yout];
% end
ObjVSel = mohupidobj(Chrom(BestJ,:));
figure(2)
plot(timef,rin,'r',timef,yout,'b');
xlabel('Time(s)');ylabel('rin,yout');
 text(0.5,0.95,['Best = ', num2str(Best(gen+1))],'Units','normalized');