Gitlab Runner Update from orc-aux-files/master:Correct the folder name for exercises 15_1,15_3,15_4

ORC/exercise-files/Exercise_material_SoSe_2021/code/E_15_1_and15_3_and_E_15_4/orc15_1_and_E_15_3_H2.m

+% ORC 15.3  :: H2 norm computation
+%
+% TUHH :: Institut for Control Systems :: Optimal and Robust Control
+% Last update: 20.05.2009
+
+load orc15_design2 CL2 Gyr2
+T = Gyr2;
+
+
+%% Using the gramians
+% with observability gramian
+Wo = gram(T,'o');  
+h2gramo = sqrt( trace(T.B'* Wo *T.B) )
+
+% with the controllability gramian
+Wc = gram(T,'c');
+h2gramc = sqrt( trace(T.C* Wc *T.C') )
+
+
+%% Using the inpulse response
+T_step = 0.001;
+t = 0:T_step:2;
+
+[g,t] = impulse(T,t); 
+
+Sum = 0; 
+for i = 1:length(t)
+    X(:,:) = g(i,:,:);
+    Sum = Sum + trace(X'*X);
+end
+h2imp = sqrt ( Sum * T_step )
+
+
+%% with the norm function
+h2norm = norm(T, 2)
+hinfnorm = norm(T, inf)

ORC/exercise-files/Exercise_material_SoSe_2021/code/E_15_1_and15_3_and_E_15_4/orc15_1_and_E_15_4_Hinf.m

+% ORC 15.4  :: H-infinity norm calculation
+%
+% TUHH :: Institut for Control Systems :: Optimal and Robust Control
+% Last update: 24.05.2016
+
+load orc15_design2 Gyr2
+T = Gyr2;
+[A,B,C,D] = ssdata(T);
+
+ 
+%% Using iterations over gamma
+eigtol = 1e-6;
+
+% tic
+for gamma = 5:-0.01:0
+    M = [A              1/gamma*B*B'
+        -1/gamma*C'*C   -A'];
+    if min(abs(real(eig(M)))) < eigtol  % check if the minimum real eig.
+                                        % value is close to the imag. axis
+        break
+    end
+end
+hinf_iter = gamma
+% toc
+
+
+%% Or using bisections over gamma
+g_max = 100;
+g_min = 0.01;
+g_tol = 0.1;
+
+eigtol = 1e-6;
+
+% tic
+while g_max - g_min > g_tol
+    figure(1); clf; sigma(T); hold on; line([1e-1, 1e4], 20*log10([g_max, g_max]), 'Color', [0.0 0.8 0.0]); line([1e-1, 1e4], 20*log10([g_min, g_min]), 'Color', [0.8 0.0 0.0]);
+    pause;
+    gamma = (g_max + g_min)/2;
+    M = [A              1/gamma*B*B'
+        -1/gamma*C'*C   -A'];
+    if min(abs(real(eig(M)))) < eigtol
+        g_min = gamma;      % there is imag. eigval.     ==> Hinf > gamma
+    else
+        g_max = gamma;      % there is no imag. eigenval ==> Hinf < gamma
+    end
+    
+end
+hinf_bis = gamma
+% toc
+
+
+%% Using the singular value plot and the norm function
+sigma(T);
+dta = ginput(1);
+hinf_sig = 10^(dta(2)/20)      % convert from log scala
+
+hinf_norm = norm(T, inf)