Table 1 DOTcvpSB typical input data structure for the drug displacement problem.

data.name

= 'DrugDisplacement';

% name of the problem

data.odes.parameters(1)

= {'A = 232'};

% constant parameters before ODE

data.odes.parameters(2)

= {'B = 46.4'};

data.odes.parameters(3)

= {'C = 2152.96'};

data.odes.res(1)

= {'((1+0.2*(y(1)+y(2)))^2/(((1+0.2*(y(1)+y(2)))^2+A+B*y(2))*((1+0.2*(y(1)+y(2)))^2+A+B*y(1))-C*y(1)*y(2)))*(((1+0.2*(y(1)+y(2)))^2+A+B*y(1))*(0.02-y(1))+B*y(1)*(u(1)-2*y(2)))'};

data.odes.res(2)

= {'((1+0.2*(y(1)+y(2)))^2/(((1+0.2*(y(1)+y(2)))^2+A+B*y(2))*((1+0.2*(y(1)+y(2)))^2+A+B*y(1))-C*y(1)*y(2)))*(((1+0.2*(y(1)+y(2)))^2+A+B*y(2))*(u(1)-2*y(2))+46.4*(0.02-y(1)))'};

data.odes.res(3)

= {'1'};

data.odes.ic

= [0.02 0.0 0.0];

% vector of initial conditions

data.odes.tf

= 300.0;

% final time

data.nlp.RHO

= 5;

% CVP discretization level

data.nlp.J0

= 'y(3)';

% performance index, min-max(performance index)

data.nlp.u0

= 4.0;

% initial guess for control values

data.nlp.lb

= 0.0;

% lower bounds for control values

data.nlp.ub

= 8.0;

% upper bounds for control values

data.nlp.solver

= 'IPOPT';

% ['FMINCON'|'IPOPT'|'SRES'|'DE'|'ACOMI'|'MISQP'|'MITS']

data.nlp.FreeTime

= 'on';

% ['on'|'off'] set 'on' if free time is considered

data.nlp.eq.status

= 'on';

% ['on'|'off'] switch on/off of the equality constraints

data.nlp.eq.NEC

= 2;

% number of active equality constraints

data.nlp.eq.eq(1)

= {'y(1)-0.02'};

% first equality constraint

data.nlp.eq.eq(2)

= {'y(2)-2.0'};

% second equality constraint

data.nlp.eq.time(1)

= data.nlp.RHO;

% to indicate that it is an end-point constraint

data.nlp.eq.time(2)

= data.nlp.RHO;

% to indicate that it is an end-point constraint

data.options.trajectories

= size(data.odes.res,2)-1;

% how many state trajectories will be displayed