CE 3.1a case 1

# CE 3.1a case 1 - disp('System is controllable.') else...

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Sheet1 Page 1 %------------------------------------------------- % CE 3.1a (case 1) %------------------------------------------------- A = [0 1 0 0 0 0 -30 -1.2 20 0.8 0 0 B = [0 0 0 1 0 0 C = [1 0 0 0 0 0 0 0 1 0 0 0 D = [0] JbkR = ss(A,B,C,D) % Define model from state-space JbkRtf = tf(JbkR) % Convert to transfer function JbkRzpk = 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 description JbkRss = ss(JbkRtf) % Convert to state-space description P = ctrb(JbkR) % Calculate % controllability % matrix P if (rank(P) == size(A,1)) % Logic to assess % controllability

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Unformatted text preview: disp('System is controllable.') else disp('System is NOT controllable.') end P1 = [B A*B] % Check P via the % formula CharPoly = poly(A) % Determine the system % characteristic polynomial a1 = CharPoly(2) % Extract a1 Pccfi = [a1 1 1 0] % matrix Pccf Tccf = P*Pccfi % Calculate the CCF % transformation matrix Accf = inv(Tccf)*A*Tccf % Transform to CCF via % formula Bccf = inv(Tccf)*B Cccf = C*Tccf Dccf = D Sheet1 Page 2 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] 0 0 0 0 0.5 0 0 0 0 0 0 0.333] 0 0 0 0 1 0] % Calculate the inverse of Sheet1 Page 3 % Define the state-space realization...
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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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CE 3.1a case 1 - disp('System is controllable.') else...

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