How to find a proper algorithm to solve this optimal control problem?
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Ehsan Ranjbari
el 13 de En. de 2022
Comentada: Ehsan Ranjbari
el 21 de En. de 2022
Hi everyone!
I am trying to find a way to solve this optimal control problem in MATLAB. The function is too complex and the using Hamiltonian in MATLAB couldn't help.The problem describes as below:
p = 100;
a = 0;
b = 0.07;
c = 0.04;
r = 0.005;
z = 0.1;
c0 = 70;
x0 = 0.4;
alpha = 0.005;
beta = 0.006;
gamma = 0.003;
delta = 0.007;
Dx = (alpha + beta*u + (gamma + delta*u)*x)*(1-x); % State Equation
f = ((p - c0*((x0/x)^z))*Dx) - (a + (b*u) + (c*u^2)); % Function inside the integral (Cost function)
% x(t0) = 0.4, x(tf) = free, t0 = 0. tf = 31
Note that the aim is to maximize the function f.
I tried to use fmincon and still the function is too complex to get an answer.
Thanks!
3 comentarios
Torsten
el 13 de En. de 2022
Sorry, but I have no experience with numerical optimal control.
So I can't give you advise in this respect.
Respuesta aceptada
Torsten
el 14 de En. de 2022
This should give you a start:
%Optimal advertising expenditure in monopoly
%% Constants
p = 100;
a = 0;
b = 0.07;
c = 0.04;
r = 0.005;
z = 0.1;
c0 = 70;
x0 = 0.4;
alpha = 0.005;
beta = 0.006;
gamma = 0.003;
delta = 0.007;
%% State equation (g)
syms x u p1
Dx = (alpha + beta*u + (gamma + delta*u)*x)*(1-x);
%% Cost function inside the integral (f)
f = ((p - c0*((x0/x)^z))*Dx) - (a + (b*u) + (c*u^2));
%% Hamiltonian %lambda_0= 1 (Normal case)
H = f + p1*Dx;
%% Costate equations
Dp1 = -diff(H,x);
%% solve for control u
du = diff(H,u);
sol_u = solve(du,u);
f = subs(f,u,sol_u)
Dp1 = subs(Dp1,u,sol_u)
rhs = [f;Dp1];
% Turn to numerical computation
fun = matlabFunction(rhs)
tmesh = linspace(0,31,150);
guess = @(x)[0.4*(1-x/31)+x/31;1]
solinit = bvpinit(tmesh,guess);
bvpfcn = @(t,y)fun(y(2),y(1));
bcfcn = @(ya,yb)[ya(1)-0.4;yb(1)-1];
sol = bvp4c(bvpfcn, bcfcn, solinit)
2 comentarios
Torsten
el 14 de En. de 2022
Since you want to maximize, you'll have to take
f = -(((p - c0*((x0/x)^z))*Dx) - (a + (b*u) + (c*u^2)));
I guess.
Más respuestas (1)
Walter Roberson
el 13 de En. de 2022
You did not say what you wanted to optimzie with respect to. If you wanted to optimize with respect to u, then see solu below.
If you wanted to optimize with respect to x (in terms of u) then I will need to do more testing.
syms x u
p = 100;
a = 0;
b = 0.07;
c = 0.04;
r = 0.005;
z = 0.1;
c0 = 70;
x0 = 0.4;
alpha = 0.005;
beta = 0.006;
gamma = 0.003;
delta = 0.007;
Dx = (alpha + beta*u + (gamma + delta*u)*x)*(1-x); % State Equation
f = ((p - c0*((x0/x)^z))*Dx) - (a + (b*u) + (c*u^2)); % Function inside the integral (Cost function)
f
Dfu = diff(f,u)
string(Dfu)
solu = simplify(solve(Dfu, u))
Dfx = diff(f,x)
string(Dfx)
3 comentarios
Torsten
el 13 de En. de 2022
Editada: Torsten
el 13 de En. de 2022
I think the problem is
Find u(t) such that
integral_{t=0}^{t=tf} ((p - c0*((x0/x(t))^z))*dx/dt) - (a + (b*u(t)) + (c*u(t)^2)) dt
is maximized under the constraint
dx/dt = (alpha + beta*u(t) + (gamma + delta*u(t))*x(t))*(1-x(t))
x(0)=0, x(tf) = free
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