Gitlab Runner Update from atc-aux-files/master:Merge branch 'update_63_64_65' into 'master'

ATC/exercise-files/MAS/6.3/solution_MAS_qcopter.m

+%% Design of a Formation Controller
+% -------------------------------------------------------------------------
+% script   : exercise_MAS_qcopter
+% -------------------------------------------------------------------------
+% Author   : Marcus Bartels
+% Version  : December 10th, 2013
+% Copyright: MB, 2013
+% -------------------------------------------------------------------------
+%
+% 1. Define the agent model given in the appendix of the Lecture Notes
+% 2. Formulate agent + uncertain topology in LFT form
+% 3. Generate a generalized plant
+% 4. Synthesize a robust formation controller
+%
+% -------------------------------------------------------------------------
+
+%% state space model of the quadrocopter
+g = 9.81;   % Gravity constant
+
+m = 0.640;  %  Mass of the Quadrocopter
+  
+A = [ 0  1  0  0  0  0  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  0 -g  0  0  0   ;
+      0  0  0  1  0  0  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  g  0   ;
+      0  0  0  0  0  1  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  1  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  1  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  0  1   ;
+      0  0  0  0  0  0  0  0  0  0  0  0 ] ;
+   
+B = [ 0  0  0  0  0 1/m 0  0  0  0  0  0   ;
+      0  0  0  0  0  0  0  1  0  0  0  0   ;
+      0  0  0  0  0  0  0  0  0  1  0  0   ;
+      0  0  0  0  0  0  0  0  0  0  0  1 ]';
+
+nx = size(A,1); % number of states
+  
+C = zeros(3,nx);
+C(1,1) = 1; % x
+C(2,3) = 1; % y
+C(3,5) = 1; % z
+
+nu = size(B,2); % number of inputs
+ny = size(C,1); % number of outputs
+
+D = zeros(ny,nu);
+
+P = ss(A,B,C,D);
+Paug = ss(A,B,[C; eye(nx)], [D; zeros(nx,nu)]);
+% Augmented plant with state vector as additional output 
+
+%% setup of the generalized plant
+% Factorize C
+[U,S,V] = svd(C);   
+Dd = U*S;
+Cd = V';
+nd = size(Cd,1); % size of Delta
+
+% Generate an LFT model of one agent
+Blft = [zeros(nx,nd), B];
+Clft = [Cd; C; eye(nx)];
+Dlft = [zeros(nd,nd),   zeros(nd,nu);
+            Dd,         zeros(ny,nu);
+        zeros(nx,nd),   zeros(nx,nu)];
+Plft = ss(A,Blft,Clft,Dlft);    
+
+% Define the shaping filters
+omega_S = 1e-3;
+M_S     = 1e-3;
+omega_KS = 1e3;
+M_KS     = 10;
+c_KS     = 1e3;
+w_S = tf(omega_S /M_S , [1 omega_S]);
+Ws = diag(ones(1,ny))*w_S;
+w_KS = (c_KS/M_KS) * tf([1 omega_KS],[1 c_KS*omega_KS]);
+Wk = diag(ones(1,nu))*w_KS;
+
+% Compose the generalized plant
+systemnames = 'Plft Ws Wk';
+inputvar    = sprintf('[wd(%d); r(%d); u(%d)]', nd,ny,nu);
+input_to_Plft = '[wd; u]';
+input_to_Ws = sprintf('[r-Plft(%d:%d)]', nd+1,nd+ny);
+input_to_Wk = '[u]';
+outputvar   = sprintf('[Plft(1:%d); Ws; Wk; r-Plft(%d:%d); -Plft(%d:%d)]', nd,nd+1,nd+ny,nd+ny+1,nd+ny+nx);
+cleanupsysic = 'yes';
+GP = sysic; % compose the defined setup
+
+NMEAS = ny+nx;  % number of measured outputs
+NCON = nu;      % number of control inputs
+
+%% Controller Synthesis
+[K,CL,gam1,INFO] = hinfsyn(GP,NMEAS,NCON,'METHOD','LMI');
+
+%% Simulation Setup
+% Define the topology
+L = [1,     0,      -1,     0;
+     0,     1,      -1,     0;
+     -1/2,  -1/2,   1,      0;
+     -1/2,  0,      -1/2,   1];
+Lq = kron(L,eye(ny));
+
+% Define the reference
+ref = [2 4 6 8]';
+iny = [1; 0; 0];    % Assign 'ref' values to x-direction of every agent
+r = kron(eye(4),iny)*ref;
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ATC/exercise-files/MAS/6.4/solution_MAS_IFFdesign.m

+%% Information Flow Filter for Formation Control
+% -------------------------------------------------------------------------
+% script   : exercise_MAS_IFFdesign
+% -------------------------------------------------------------------------
+% Author   : Marcus Bartels
+% Version  : December 10th, 2015
+% Copyright: MB, 2015
+% -------------------------------------------------------------------------
+%
+% 1. Formulate information flow filter + uncertain topology in LFT form
+% 2. Generate a generalized plant
+% 3. Synthesize a robust formation controller
+%
+% -------------------------------------------------------------------------
+%% Shaping filter definition
+omega_Sf = 1e-2;
+M_Sf = 3e-2;
+Wsf = tf(omega_Sf /M_Sf , [1 omega_Sf]);
+
+%% Generalized Plant setup
+Pf = tf(1); % Here an auxiliary filter could be inserted to make generalized plant strictly proper
+systemnames = 'Wsf Pf';
+inputvar    = sprintf('[w(%d); r(%d); p(%d)]', 1,1,1);
+input_to_Pf = sprintf('[w+r-p]');
+input_to_Wsf = sprintf('[Pf]');
+outputvar   = sprintf('[r-p; Wsf; Pf]');
+cleanupsysic = 'yes';
+GPf = sysic; % compose the defined setup
+
+NMEAS = 1;  % number of measured outputs
+NCON = 1;   % number of control inputs
+
+%% Information Flow Filter synthesis
+[f,CL,gam1,INFO] = hinfsyn(GPf,NMEAS,NCON,'METHOD','LMI');
+
+%% Simulation setup
+L = [1,    -1/2, -1/2, 0,   0;
+     0,      1,    0, -1,   0;
+     -1/2,   0,    1, -1/2, 0;
+     0     -1/2, -1/2, 1,   0;
+     0     -1/2,   0, -1/2, 1];
+ 
+% modified Laplacian for additional agent
+L6 = [  1,    -1/3, -1/3, 0,   0,   -1/3;
+        0,      1,    0, -1/2, 0,   -1/2;
+        -1/2,   0,    1, -1/2, 0,   0;
+        0     -1/2, -1/2, 1,   0,   0;
+        0     -1/2,   0, -1/2, 1,   0;
+        0,      0,    0,  0,   0,   1];
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ATC/exercise-files/MAS/6.5/exercise_MAS_IFFdist.m

+%%  Disturbance Rejection in Formation Control
+% -------------------------------------------------------------------------
+% script   : exercise_MAS_IFFdist
+% -------------------------------------------------------------------------
+% Author   : Marcus Bartels
+% Version  : January 12th, 2015
+% Copyright: MB, 2015
+% -------------------------------------------------------------------------
+%% Initialization
+close all
+
+% Define number of agents
+N = 5;
+% Define plant model
+m = 10;
+b = 0.5;
+c = 0;
+PA = [0, 1; -c/m, -b/m];
+PB = [0; 1/m];
+PC = [1 0];
+PD = 0;
+P = ss(PA,PB,PC,PD);
+nx = size(PA,1);    % number of states
+% Define controller
+K = 20*tf([1 0.05],[1 2.4]);
+[KA,KB,KC,KD] = ssdata(K);
+
+% Define the Laplacian
+L = [1,    -1/2, -1/2, 0,   0;
+     0,      1,    0, -1,   0;
+     -1/2,   0,    1, -1/2, 0;
+     0     -1/2, -1/2, 1,   0;
+     0     -1/2,   0, -1/2, 1];
+la = sort(eig(L));
+%%  setup information flow filter and local controller
+f = tf([1 8.5],[1e-4 1 0.01]);
+Kl = 0.15*tf([60 1],[0.6 1]);
+
+%% modified Laplacian for additional agent
+L6 = [  1,    -1/3, -1/3, 0,   0,   -1/3;
+        0,      1,    0, -1/2, 0,   -1/2;
+        -1/2,   0,    1, -1/2, 0,   0;
+        0     -1/2, -1/2, 1,   0,   0;
+        0     -1/2,   0, -1/2, 1,   0;
+        0,      0,    0,  0,   0,   1];
\ No newline at end of file