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PID tuning controller by Bacterial foraging

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12 Jun 2008 (Updated )

tuning the PID controller to get minimum error

Tunning of PID controller using Bacterial foraging

Tunning of PID controller using Bacterial foraging

Author: Wael Mansour (wael192@yahoo.com)

MSc Student, Electrical Enginering Dept, Faculty of Engineering Cairo University, Egypt

%Initialization
clear all
clc
p=2;                         % dimension of search space
s=10;                        % The number of bacteria
Nc=5;                       % Number of chemotactic steps
Ns=4;                        % Limits the length of a swim
Nre=4;                       % The number of reproduction steps
Ned=2;                       % The number of elimination-dispersal events
Sr=s/2;                      % The number of bacteria reproductions (splits) per generation
Ped=0.25;                    % The probabilty that each bacteria will be eliminated/dispersed
c(:,1)=0.05*ones(s,1);       % the run length
for m=1:s                    % the initital posistions
    P(1,:,1,1,1)= 50*rand(s,1)';
    P(2,:,1,1,1)= .2*rand(s,1)';
   %P(3,:,1,1,1)= .2*rand(s,1)';
end
%Main loop


%Elimination and dispersal loop
for ell=1:Ned


%Reprodution loop


    for K=1:Nre

%  swim/tumble(chemotaxis)loop

        for j=1:Nc

            for i=1:s
                J(i,j,K,ell)=tracklsq(P(:,i,j,K,ell));

% Tumble


                Jlast=J(i,j,K,ell);
                Delta(:,i)=(2*round(rand(p,1))-1).*rand(p,1);
                P(:,i,j+1,K,ell)=P(:,i,j,K,ell)+c(i,K)*Delta(:,i)/sqrt(Delta(:,i)'*Delta(:,i)); % This adds a unit vector in the random direction

% Swim (for bacteria that seem to be headed in the right direction)

                J(i,j+1,K,ell)=tracklsq(P(:,i,j+1,K,ell));
                m=0;         % Initialize counter for swim length
                    while m<Ns
                          m=m+1;
                          if J(i,j+1,K,ell)<Jlast
                             Jlast=J(i,j+1,K,ell);
                             P(:,i,j+1,K,ell)=P(:,i,j+1,K,ell)+c(i,K)*Delta(:,i)/sqrt(Delta(:,i)'*Delta(:,i)) ;
                             J(i,j+1,K,ell)=tracklsq(P(:,i,j+1,K,ell));
                          else
                             m=Ns ;
                          end

                    end
                J(i,j,K,ell)=Jlast;
                sprintf('The value of interation i %3.0f ,j = %3.0f  , K= %3.0f, ell= %3.0f' , i, j, K ,ell );

            end % Go to next bacterium

        end  % Go to the next chemotactic


%Reprodution
        Jhealth=sum(J(:,:,K,ell),2);              % Set the health of each of the S bacteria
        [Jhealth,sortind]=sort(Jhealth);          % Sorts the nutrient concentration in order of ascending
        P(:,:,1,K+1,ell)=P(:,sortind,Nc+1,K,ell);
        c(:,K+1)=c(sortind,K);                    % And keeps the chemotaxis parameters with each bacterium at the next generation


%Split the bacteria (reproduction)
            for i=1:Sr
                P(:,i+Sr,1,K+1,ell)=P(:,i,1,K+1,ell); % The least fit do not reproduce, the most fit ones split into two identical copies
                c(i+Sr,K+1)=c(i,K+1);
            end
        end %  Go to next reproduction


%Eliminatoin and dispersal
        for m=1:s
            if  Ped>rand % % Generate random number
                P(1,:,1,1,1)= 50*rand(s,1)';
                P(2,:,1,1,1)= .2*rand(s,1)';
               %P(3,:,1,1,1)= .2*rand(s,1)';
            else
                P(:,m,1,1,ell+1)=P(:,m,1,Nre+1,ell); % Bacteria that are not dispersed
            end
        end
    end % Go to next elimination and disperstal

%Report
           reproduction = J(:,1:Nc,Nre,Ned);
           [jlastreproduction,O] = min(reproduction,[],2);  % min cost function for each bacterial
           [Y,I] = min(jlastreproduction);
           pbest=P(:,I,O(I,:),K,ell);
           Kp= pbest(1,:)
           Kd=pbest(2,:)
Kp =

    0.9290


Kd =

    0.6758

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