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%% Create State-Space Model with Both Fixed and Tunable Parameters % This example shows how to create a state-space |<docid:control_ref.bswj_ky-1>| model % having both fixed and tunable parameters. % % $$A = \left[ {\begin{array}{*{20}{c}} % 1&{a + b}\\ % 0&{ab} % \end{array}} \right],\quad B = \left[ {\begin{array}{*{20}{c}} % { - 3.0}\\ % {1.5} % \end{array}} \right],\quad C = \left[ {\begin{array}{*{20}{c}} % {0.3}&0 % \end{array}} \right],\quad D = 0,$$ % % where _a_ and _b_ are tunable parameters, whose initial values are |-1| % and |3|, respectively. %% % Create the tunable parameters using |<docid:control_ref.bswkh7a-1>|. a = realp('a',-1); b = realp('b',3); %% % Define a generalized matrix using algebraic expressions of |a| and |b|. A = [1 a+b;0 a*b]; %% % |A| is a generalized matrix whose |Blocks| property contains |a| and |b|. % The initial value of |A| is |[1 2;0 -3]|, from the initial values of |a| % and |b|. %% % Create the fixed-value state-space matrices. B = [-3.0;1.5]; C = [0.3 0]; D = 0; %% % Use |<docid:control_ref.f4-390421>| to create the state-space model. sys = ss(A,B,C,D) %% % |sys| is a generalized LTI model (|genss|) with tunable parameters |a| % and |b|.