How to get around the " Attempted to access para(2); index out of bounds because numel(para)=1." error that appears in the following code?

I have a code which has three parts in it viz. the main PSO code, the function and the Simulink block. On running the main PSO code, I am getting the following error

Attempted to access para(2); index out of bounds because numel(para)=1.

Error in sofunc2 (line 6)
         r2 = para(2)

Error in sosmc_sch1_c2 (line 55)
         obj_value(i)=sofunc2(current_position{:,i});

The main PSO code is as below

tic
clear all
close all
clc
% Initializing variables
S=10;         % no of swarm particles
d=3;           % dimension of swarm particles
c1=2;          % self confidence parameter
c2=1;          % swarm confidence parameter
C=1;           % constriction factor 
LB=[0 0 0];    %lower bounds of variables
UB=[1 1 1];  %upper bounds of variables
wmax=0.9;         % maximum inertia weight
wmin=0.4;         % minimum inertia weight
Xmax=1;       % maximum position
iter=1;        % initial iteration
R1=rand();
R2=rand();
tolerance=1;
Maxiter=40;   % maximum number of iteration
maxrun=5;
dt=1;
particle_best=cell(1,S);
particle_best_value=ones(1,S)*1E5;
global_best_value=1E5;
global_best=zeros(1,d);
obj_value=zeros(1,S);        % Objective function value of particles
%%%%%%%%
current_position=cell(1,S);    % particle position
velocity=cell(1,S);           % particle velocity
dummy=zeros(1,length(d));     % dummy list

% Initialize particle position and velocity
for run=1:maxrun
run
for i=1:S
    for j=1:d
        dummy(j)=round(LB(j)+rand()*(UB(j)-LB(j)));
    end
    current_position{i}=dummy;
    velocity{i}=current_position{i}/dt;   
end
while iter <= Maxiter && tolerance > 0.01

       for i=1:S   
           for j=1:d
                if current_position{i}<LB(j)               %%handling boundary conditions
                   current_position{i}=LB(j);
            elseif current_position{i}>UB(j)
               current_position{i}=UB(j);
                end 
           end
       end 
       for i=1:S
           obj_value(i)=sofunc2(current_position{:,i});
       end
       for i=1:S
          if obj_value(i) < particle_best_value(i)           % finding best local
              particle_best{i}= current_position{i};
              particle_best_value(i)=obj_value(i);
          end
       end
        [fmin,index]=min(obj_value); % finding out the best particle
        ffmin(iter,run)=fmin; % storing best fitness
        ffite(run)=iter; % storing iteration count

          if  min(obj_value)< global_best_value                           % finding best global
              global_best=current_position{obj_value==min(obj_value)};          % updating gbest and best fitness
              global_best_value=min(obj_value);
              fmin0=global_best_value;
          end
          for i=1:S
          w=wmax-((wmax-wmin)/Maxiter)*iter;
          velocity{i}=C*(w*velocity{i}+c1*R1*(particle_best{i}-current_position{i})+c2*R2*(global_best-current_position{i}));
          current_position{i}=current_position{i}+velocity{i};
          end
              % calculating tolerance
          if iter>20;
              tolerance=abs(ffmin(iter-20,run)-fmin0)
          end

           % displaying iterative results
          if iter==1
             disp(fprintf('Iteration Best particle Objective fun'));
          end
             disp(fprintf('%8g %8g %8.4f',iter,index,fmin0));
             iter=iter+1;

          subplot(1,2,1);
          plot(current_position{i}(1),'rO')
          xlim([-5*Xmax    5*Xmax])
          ylim([-5*Xmax    5*Xmax])
          title('Particles instant location')
          grid on
          hold on;
          hold off;
          subplot(1,2,2);
          plot(iter,global_best_value,'bO')
          grid on
          hold on
          xlim([0 Maxiter]);
          title('Best Particle value histogram');
          xlabel('iteration no')
          ylabel('global best value')
  %         pause(0.05)
  %         disp(['BEST PARTICLE VALUE >> ' num2str(global_best_value)])
  end
          % pso algorithm-----------------------------------------------------end
          global_best;
          fvalue=global_best_value;
          fff(run)=fvalue;
          rgbest(run,:)=global_best;
          disp(sprintf('--------------------------------------'));
  %         disp(['BEST PARTICLE POSITION >> ' num2str(global_best)])
  end

% pso main program------------------------------------------------------end
disp(sprintf('\n'));
disp(sprintf('*********************************************************'));
disp(sprintf('Final Results-----------------------------'));
[bestfun,bestrun]=min(fff)
best_variables=rgbest(bestrun,:)
disp(sprintf('*********************************************************'));
toc
% PSO convergence characteristic
plot(ffmin(1:ffite(bestrun),bestrun),'-k');
xlabel('Iteration');
ylabel('Fitness function value');
title('PSO convergence characteristic')
%####################################

The function is made in a seperate matlab file as shown below

function F = sofunc2(para)
           % Track the output of optsim to a signal of 1

             % Variables a1 and a2 are shared with RUNTRACKLSQ
             c2 = para(1)
             r2 = para(2)
             W2 = para(3)

             disp(sprintf('The value of parameters c2= %3.0f, r2= %3.0f, W2= %3.0f', para(1),para(2),para(3))); 
             % Compute function value
             simopt = simset('solver','ode1','SrcWorkspace','current','DstWorkspace','current');  % Initialize sim options
             [tout,xout,yout] = sim('sosmc_c2',[0 200],simopt);
    %         e=yout-1 ;  % compute the error 
    %         sys_overshoot=max(yout)-2 % compute the overshoot
        if para(1)<0 || para(1)>5
           penalty=500;
        elseif para(2)<0 || para(2)>5
            penalty=500;
        elseif para(3)<0 || para(3)>5
            penalty=500;
        else
            penalty=0;
        end 

          A=5; %B=1;C=5;
          F=int_abs_error*A+penalty 

        end

The simulink block (attached) contains the model whose parameters are being optimized with the PSO code. All the three parts need to be kept in the same folder for the purpose of running. Please help me figure out what is wrong with it and how to tackle it.

[Mangesh modak]

i think first you should check that current_position is cell and lb and ub are matrices