Page 115 - Control Theory in Biomedical Engineering

Modeling and optimal control of cancer-immune system 101

xlabel (’ Time ( days )’)
ylabel (’ Effector Cells, E ( t )’)
grid

figure (2)
hold off
plot ( r, T,’ r –.’,’ LineWidth ’,3)
hold on
plot ( sol . x, sol . y (2,:),’ LineWidth ’,2)
legend (’ With Control ’,’ Without Control ’);
xlim ([0 30])
xlabel (’ Time ( days )’)
ylabel (’ Tumour Cells, T ( t )’)
grid

figure (3)
hold off
plot ( r, v,’ r ––’,’ LineWidth ’,3)
hold on
bar ( r (100:900:10001), v (100:900:10001),’ barwidth ’,.1)
xlim ([0 30])
xlabel (’ Time ( days )’)
ylabel (’ Chemotherapy Control, V ( t )’)
grid
hold off
%
figure (4)
hold off
plot ( r, w,’ r ––’,’ LineWidth ’,3)
hold on
bar ( r (100:900:10001), w (100:900:10001),’ barwidth ’,.1)
xlim ([0 30])
xlabel (’ Time ( days )’)
ylabel (’ Imunotherapy Control, W ( t )’)
grid
hold off
end
%

function dy = Rihan ( t, y, ylag ) % exam1f ( t, y, Z, r1, k1, r2, a, mu1,
e, k2, mu2 )
% ylag = Z (:,1);
dy = zeros (2,1);