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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|.