MATLAB CONTROL SYSTEM TOOLBOX 9 Dokumentacja Pobierz pdf (Strona 239)

Kalman Filtering

SimModel.outputname

You are now ready to simulate the filter behavior. Generate a sinusoidal input

and process and measurement noise vectors and .

t = [0:100]';

u = sin(t/5);

n = length(t)

randn('seed',0)

w = sqrt(Q)*randn(n,1);

v = sqrt(R)*randn(n,1);

Now simulate with lsim.

[out,x] = lsim(SimModel,[w,v,u]);

y = out(:,1); % true response

ye = out(:,2); % filtered response

yv = y + v; % measured response

and compare the true and filtered responses graphically.

subplot(211), plot(t,y,'--',t,ye,'-'),

xlabel('No. of samples'), ylabel('Output')

title('Kalman filter response')

subplot(212), plot(t,y-yv,'-.',t,y-ye,'-'),

MATLAB CONTROL SYSTEM TOOLBOX 9 Dokumentacja Strona 239