diff --git a/DistributedMinimaxAdaptiveControl.m b/DistributedMinimaxAdaptiveControl.m
index 3086f171e0e8f25f625ed18fafb251c84558b289..a0d2cd3c472c48e8be5509189782b32e621fa67f 100644
--- a/DistributedMinimaxAdaptiveControl.m
+++ b/DistributedMinimaxAdaptiveControl.m
@@ -358,42 +358,34 @@ hold on;
 tvec = 0:T; 
 % Prepare the legend text for plotting
 i = 1;
-text_1 = '$\left \Vert x^{\dagger}_{';
-text_2 = num2str(i);
-text_3 = '}';
-text1 = strcat(text_1, strcat(text_2, text_3));
-text_1 = ' - x^{\star}_{';
-text_2 = num2str(i);
+text_1 = '$x^{\dagger} - x^{\star}$';
 if(disturbFlag == 1)
-    text_3 = '} \right \|_{1}$: white noise $w$';
+    text_3 = ': white noise $w$';
 elseif(disturbFlag == 2)
-    text_3 = '} \right \|_{1}$: sinusoidal $w$';
+    text_3 = ': sinusoidal $w$';
 elseif(disturbFlag == 3)
-    text_3 = '} \right \|_{1}$: step $w$';
+    
+    text_3 = ': step $w$';
 end
-text2 = strcat(text1, strcat(text_1, strcat(text_2, text_3)));
+text2 = strcat(text_1, text_3);
 legendInfos{i} = [text2]; 
-plot(tvec, abs(x_minmax(1,:) - x_hinfty(1,:))', 'o-');
+shadedErrorBar(tvec,x_minmax - x_hinfty,{@mean,@std}, 'lineprops','-b','patchSaturation',0.33)
 
 tvec = 0:T-1; 
 % Prepare the legend text for plotting
 i = 1;
-text_1 = '$\left \Vert u^{\dagger}_{';
-text_2 = num2str(i);
-text_3 = '}';
-text1 = strcat(text_1, strcat(text_2, text_3));
-text_1 = ' - u^{\star}_{';
-text_2 = num2str(i);
+text_1 = '$u^{\dagger} - u^{\star}$';
 if(disturbFlag == 1)
-    text_3 = '} \right \|_{1}$: white noise $w$';
+    text_3 = ': white noise $w$';
 elseif(disturbFlag == 2)
-    text_3 = '} \right \|_{1}$: sinusoidal $w$';
+    text_3 = ': sinusoidal $w$';
 elseif(disturbFlag == 3)
-    text_3 = '} \right \|_{1}$: step $w$';
+    text_3 = ': step $w$';
 end
-text2 = strcat(text1, strcat(text_1, strcat(text_2, text_3)));
+text2 = strcat(text_1, text_3);
 legendInfos{i+1} = [text2]; 
-plot(tvec, abs(U_minmax(1,:) - u_hinfty(1,:))', 'o-');
+shadedErrorBar(tvec,U_minmax-u_hinfty,{@mean,@std},'lineprops','-r','patchSaturation',0.33)
+
 
 xlabel('Time');
 legend(legendInfos, 'interpreter', 'latex');
@@ -406,45 +398,3 @@ set(a, 'FontSize', 50);
 % Convert matlab figs to tikz for pgfplots in latex document.
 matlab2tikz('figurehandle',figure1,'filename','statesControlsDiff.tex' ,'standalone', true, 'showInfo', false);
 
-% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% % %% Compute the cumulative regret
-% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% 
-% % Define design parameters.
-% Q = eye(n);         % State penalty matrix 
-% R = eye(m);         % Input penalty matrix 
-% 
-% % Initiate model based regret to zero for each model
-% cumulativeRegret = zeros(T+1,1);
-% 
-% % Loop through all finite set of linear system models  
-% inputSum = 0;
-% stateSum = 0;
-% % Loop through the entire time horizon
-% for t = 1:T+1
-%     % compute u'Ru and add it to control sum
-%     if(t < T+1)
-%         inputSum = inputSum + (U_minmax(:,t) - u_hinfty(:,t))'*R*(U_minmax(:,t) - u_hinfty(:,t));
-%     end
-%     % compute x'Qx and add it to state sum
-%     stateSum = stateSum + (x_minmax(:,t) - x_hinfty(:,t))'*Q*(x_minmax(:,t) - x_hinfty(:,t));
-% 
-%     % Record the regret incurred upto that time
-%     cumulativeRegret(t, 1) = stateSum + inputSum; 
-% end
-% 
-% %% Plot the regret vs time
-% Tvec = 0:T;
-% figure3 = figure('Color',[1 1 1]);
-% plot(Tvec, cumulativeRegret, '-ob');
-% xlabel('Time');
-% ylabel('Regret');
-% hold off;
-% a = findobj(gcf, 'type', 'axes');
-% h = findobj(gcf, 'type', 'line');
-% set(h, 'linewidth', 4);
-% set(a, 'linewidth', 4);
-% set(a, 'FontSize', 40);
-% 
-% %% Convert matlab figs to tikz for pgfplots in latex document.
-% matlab2tikz('figurehandle',figure3,'filename','CumRegret.tex' ,'standalone', true, 'showInfo', false);
\ No newline at end of file