clear;

sample=.1;

% Vary the size of the step input here
step_mag=.25;

% Vary the noise magnitude here
noisemag=0;
noise=(noisemag)^2;

sim('id_p3_mod',20)

figure(1)
subplot(211)
plot(t,x1,'o')
subplot(212)
plot(t,u,'x')

% Put in an algorithm to find a transfer function from phi and Y matrices here
% Make sure to use the variables Y, phi, theta as appropriate, and name tbe
% transfer function sys


% This will plot a step response due to the step of the magnitude above
% (by linear property mutliply system by the magnitude, since the step
% function automatically applies a step size of 1)

figure(2)
step(step_mag*sys,20)

% Compare y and <phi,theta> here
figure(3)
plot(t,[Y,phi*theta])
title(sprintf('Error %g %%',norm(Y-phi*theta)/norm(Y)))