[Scilab-users] PID tuning with Optimization

[Gona]

Hi,

I found out whats wrong basically in my system I have modeled. I hadnt had
the input pushed in to the workspace variable block_output.

I fixed that issue and now the system and output look like this.

Note: I used D gain fixed at 1 as my system is unstable without D

<http://mailinglists.scilab.org/file/n4030515/SystemDiagram-Opt.gif> 
<http://mailinglists.scilab.org/file/n4030515/BeforeOptimization.gif> 

When I initialized the x0 variable to [1;5] (Initial P and I gains), The
optimization routine calculated the optimum gains 1 and 5 for P and I
respectively after 90 iterations.
*
Evaluation 90 - P = 0.999831 I = 4.997351 y = 0.007559 (y_error = 0.015119,
y_diff = 0.000000)
*
and the system response for the square wave looks like this
<http://mailinglists.scilab.org/file/n4030515/BeforeOpt-Prog.gif> 

Then I tried to initialize the x0 variable to [1;1] and started the
optimization routine; after 72 iterations I got 1 for P and 1 for I as
optimal gains.
*
Evaluation 71 - P = 0.999973 I = 1.001996 y = 0.240250 (y_error = 0.446943,
y_diff = 0.033557)
Evaluation 72 - P = 0.999973 I = 0.997996 y = 0.240493 (y_error = 0.447429,
y_diff = 0.033557)
*

1. Why is that the optimization routine seems to take optimal values very
close to the initially given values. ? I am not a pro but I guess it might
have something to do with quasi-Newton method which had been used in this
example as its only possible to find local minima ? In this case do we need
to guess the correct value approximately before running the optimization ?
 
2. How can I incorporate D gain in to this.

Thanks a lot in advance.





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