NE3.2c - %------------------------------------------------%...

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Unformatted text preview: %------------------------------------------------% CME 1.1 (required for CME 3.1 %------------------------------------------------A = [-1 0;0 -2]; % Define the state-space realization B = [1;sqrt(2)]; C = [1 -(sqrt(2)/2)]; D = [0]; JbkR = ss(A,B,C,D); % Define model from state-space JbkRtf = tf(JbkR); % Convert to t ransfer function JbkRzpk = zpk(JbkR); % Convert to zero-pole description [ num,den] = tfdata(JbkR,'v'); % Extract t ransfer function description [z,p,k] = zpkdata(JbkR,'v'); % Ext ract zero-pole description JbkRss = ss(JbkRtf) % Convert to state-space description %-----------------------------------------------------% CME 3.1 %-----------------------------------------------------P = ctrb(JbkR); % Calculate % controllability % matr ix P if (rank(P) == size(A,1)) % Logic to assess % controllability 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]; % Calculate the inverse of % matr ix Pccf Tccf = P*Pccfi; % Calculate the CCF % t ransformation mat rix Accf = inv(Tccf)*A*Tccf; % Transform to CCF via % formula Bccf = inv(Tccf)*B; Cccf = C*Tccf; Dccf = D; C ME 3.1a The System is controllable C M 3.1b Cccf = 1.0 0.000 ...
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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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NE3.2c - %------------------------------------------------%...

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