CE3.1a - CE 3.1a(case 1-A =[0 1 0 0 0 0-30-1.2 20 0.8 0 0;0 0 0 1 0 0;10 0.4-25-1 15 0.6 0 0 0 0 0 1 0 0 10 0.4-23.33.93 B =[0 0 0;1 0 0;0 0 0;0

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Unformatted text preview: %-------------------------------------------------% CE 3.1a (case 1)%-------------------------------------------------A = [0 1 0 0 0 0;-30 -1.2 20 0.8 0 0;0 0 0 1 0 0;10 0.4 -25 -1 15 0.6; 0 0 0 0 0 1; 0 0 10 0.4 -23.33 -.93]; B = [0 0 0;1 0 0;0 0 0;0 0.5 0;0 0 0;0 0 0.333]; % Define the state-space realizationC = [1 0 0 0 0 0;0 0 1 0 0 0;0 0 0 0 1 0];D = [0];JbkR = ss(A,B,C,D); % Define model from state-spaceJbkRtf = tf(JbkR); % Convert to transfer functionJbkRzpk = zpk(JbkR); % Convert to zero-pole description[num,den] = tfdata(JbkR,'v'); % Extract transfer function description[z,p,k] = zpkdata(JbkR,'v'); % Extract zero-pole descriptionJbkRss = ss(JbkRtf) % Convert to state-space descriptionP = ctrb(JbkR); % Calculate% controllability% matrix Pif (rank(P) == size(A,1)) % Logic to assess% controllabilitydisp('System is controllable.');elsedisp('System is NOT controllable.');endP1 = [B A*B]; % Check P via the% formula CharPoly = poly(A); % Determine the system% characteristic polynomial...
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This note was uploaded on 09/14/2011 for the course ELEN 236 taught by Professor Dr.migdathodzic during the Spring '11 term at Santa Clara.

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CE3.1a - CE 3.1a(case 1-A =[0 1 0 0 0 0-30-1.2 20 0.8 0 0;0 0 0 1 0 0;10 0.4-25-1 15 0.6 0 0 0 0 0 1 0 0 10 0.4-23.33.93 B =[0 0 0;1 0 0;0 0 0;0

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