See example in <literal>lqg2stan</literal>.
</para>
</refsection>
+
+ <refsection>
+ <title>Examples</title>
+ <programlisting role="example"><![CDATA[
+ s=poly(0,'s');
+ Plant=syslin('c',[1/(s+1)*s/(s-1)^2]); //Nominal Plant
+ P22=tf2ss(Plant); //...in state-space form
+ [ny,nu,nx]=size(P22);
+ rand('seed',0);rand('normal');
+ bigQ=rand(nx+nu,nx+nu);
+ bigQ=bigQ*bigQ';
+ bigR=rand(nx+ny,nx+ny);
+ bigR=bigR*bigR'; //random weighting matrices
+ [Plqg,r]=lqg2stan(P22,bigQ,bigR); //LQG pb as a standard problem
+ Klqg=lqg(Plqg,r); //Controller
+ spec(h_cl(Plqg,r,Klqg)) //Check internal stability
+ [Slqg,Rlqg,Tlqg]=sensi(P22,Klqg); //Sensitivity functions
+ frq=logspace(-3,3); //10^-3 to 10^3
+ y=svplot(Slqg); //Computes singular values;
+ gainplot(frq,y) //Plot sing. values
+ ]]></programlisting>
+ <scilab:image>
+ s=poly(0,'s');
+ Plant=syslin('c',[1/(s+1)*s/(s-1)^2]); //Nominal Plant
+ P22=tf2ss(Plant); //...in state-space form
+ [ny,nu,nx]=size(P22);
+ rand('seed',0);rand('normal');
+ bigQ=rand(nx+nu,nx+nu);
+ bigQ=bigQ*bigQ';
+ bigR=rand(nx+ny,nx+ny);
+ bigR=bigR*bigR'; //random weighting matrices
+ [Plqg,r]=lqg2stan(P22,bigQ,bigR); //LQG pb as a standard problem
+ Klqg=lqg(Plqg,r); //Controller
+ spec(h_cl(Plqg,r,Klqg)) //Check internal stability
+ [Slqg,Rlqg,Tlqg]=sensi(P22,Klqg); //Sensitivity functions
+ frq=logspace(-3,3); //10^-3 to 10^3
+ y=svplot(Slqg); //Computes singular values;
+ gainplot(frq,y) //Plot sing. values
+ </scilab:image>
+ </refsection>
<refsection role="see also">
<title>See Also</title>
<simplelist type="inline">