mirror of
https://github.com/KevinMidboe/linguist.git
synced 2025-10-29 17:50:22 +00:00
Added matlab code samples.
All of these code samples currently are mis-identified in my repositories. I'm donating them to the cause.
This commit is contained in:
57
samples/Matlab/fit_adapt.m
Normal file
57
samples/Matlab/fit_adapt.m
Normal file
@@ -0,0 +1,57 @@
|
||||
data = load_data('jason_adapt.mat');
|
||||
|
||||
t0 = 0;
|
||||
t1 = 30;
|
||||
t2 = 60;
|
||||
t3 = 90;
|
||||
|
||||
dataPlantOne = data(1:t1 / data.Ts);
|
||||
dataAdapting = data(t1 / data.Ts:t2 / data.Ts);
|
||||
dataPlantTwo = data(t2 / data.Ts:end);
|
||||
|
||||
% k1, k2, k3, k4, tau, zetanm, wnm, zetafs, wfs
|
||||
|
||||
% ron's guess
|
||||
guessPlantOne = [4.85, 1.79, 20, 20, 0.2, 0.707, 10, 0.707, 65];
|
||||
% best solution from ron's guess
|
||||
%guessPlantOne = [4.1129, 2.1327, 52.3747, 48.6997, 0.2, 0.707, 10, 0.707, 65];
|
||||
resultPlantOne = find_structural_gains(dataPlantOne, guessPlantOne, 1);
|
||||
[yh, fit, x0] = compare(dataPlantOne, resultPlantOne.fit);
|
||||
display(sprintf('The self validation VAF is %f.', fit(1, 1, 1)))
|
||||
|
||||
% ron's guess
|
||||
guessPlantTwo = [3.36, 9.49, 20, 0, 0.2, 0.707, 10, 0.707, 65];
|
||||
% best solution from ron's guess
|
||||
%guessPlantTwo = [2.6686, 7.0431, 14.4623, 3.1532, 0.2, 0.707, 10, 0.707, 65];
|
||||
resultPlantTwo = find_structural_gains(dataPlantTwo, guessPlantTwo, 5);
|
||||
[yh, fit, x0] = compare(dataPlantTwo, resultPlantTwo.fit);
|
||||
display(sprintf('The self validation VAF is %f.', fit(1, 1, 1)))
|
||||
|
||||
% compute the slope and offset for each gain for initial guesses
|
||||
kP1 = resultPlantOne.fit.par(1:4);
|
||||
kP2 = resultPlantTwo.fit.par(1:4);
|
||||
gainSlopeOffset = [t1 * eye(4), eye(4); t2 * eye(4), eye(4)] \ [kP1; kP2];
|
||||
|
||||
aux.pars = guessPlantOne; % this only uses tau through wfs
|
||||
aux.timeDelay = true;
|
||||
aux.plantFirst = 1; % 1 / s
|
||||
aux.plantSecond = 5; % 5 / (s + 10)
|
||||
% compute the slope and offset of the plant for t1 < t < t2
|
||||
plantOneSlopeOffset = [t1, 1; t2, 1] \ [1; 0];
|
||||
plantTwoSlopeOffset = [t1, 1; t2, 1] \ [0; 1];
|
||||
aux.m = [plantOneSlopeOffset(1); plantTwoSlopeOffset(1)];
|
||||
aux.b = [plantOneSlopeOffset(2); plantTwoSlopeOffset(2)];
|
||||
|
||||
%[dx, y] = adapting_structural_model(45, ones(8, 1), 10, gainSlopeOffset, {aux});
|
||||
|
||||
% NOTE: 'FileArgument' has to be a cell array, the is why aux is in
|
||||
% brackets. Also, if you pass the parameters in as a vector here, as I have,
|
||||
% they get mapped to a structure and your ode file/function must accept each
|
||||
% parameter as individual arguments.
|
||||
mod = idnlgrey('adapting_structural_model', [1, 1, 8], gainSlopeOffset, ...
|
||||
zeros(8, 1), 0, 'FileArgument', {aux}, 'InputName', 'thetac', ...
|
||||
'OutputName', 'theta');
|
||||
|
||||
fit = pem(dataAdapting, mod);
|
||||
|
||||
compare(dataAdapting, fit);
|
||||
Reference in New Issue
Block a user