[General] Code Tmax sun occult mission
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@ocots ya está trabajando en esto.
Desde el 5/9/2025.
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Descripción
The problem is formulated in terms of "what is the minimum amount of thrusters needed for relations these two points fixed in time and state (position & velocity), mass is free"
@jbcaillau
using SPICE
using OptimalControl
using NLPModelsIpopt
using JLD2
using OrdinaryDiffEq
using DataInterpolations
using CSV
using JLD2
using Plots
using Plots.PlotMeasures # for leftmargin, bottommargin
using LaTeXStrings
# SPICE Downloads
using Downloads: download
# SPICE files
const LSK = "https://naif.jpl.nasa.gov/pub/naif/generic_kernels/lsk/naif0012.tls"
const SPK = "https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/planets/de440.bsp"
const PCK = "https://naif.jpl.nasa.gov/pub/naif/generic_kernels/pck/pck00010.tpc"
# Download kernels
download(LSK, "naif0012.tls")
download(SPK, "de440.bsp")
download(PCK, "pck00010.tpc")
furnsh("naif0012.tls") # Leap seconds kernel
furnsh("de430.bsp")
furnsh("pck00010.tpc") # PCK kernel for planetary constants
# Astrodynamical parameters
G = 6.6743e-11 / 1000^3 # km^3 kg^-1 s^-2
M_moon = 7.346e22 # kg
M_earth = 5.972168e24 # kg
M_sun = 1.989e30 # kg
AU = 1.495978707e11 / 1e3 # km
LU = 384399 # km
TU = sqrt(LU^3 / G / (M_moon + M_earth))
MUnit = M_moon + M_earth
mu_Earth = 3.9860044188e14 / 1000^3 / LU^3 * TU^2
mu_Moon = 4.90486959e12 / 1000^3 / LU^3 * TU^2
mu_Sun = 1.327124400189e20 / 1000^3 / LU^3 * TU^2
mass_moon = M_moon / MUnit
mass_earth = M_earth / MUnit
mass_sun = M_sun / MUnit
# Spacecraft parameters
g0 = 9.80665 / 1000 / LU * TU^2
Isp = 1660 / TU
wet_mass = 400 / MUnit
fuel_mass = 90 / MUnit
dry_mass = wet_mass - fuel_mass
Tmax = 0.090 / 1000 / MUnit / LU * TU^2 #thrust force in N
Q = Tmax / Isp / g0
mass_scaling_factor = dry_mass + fuel_mass
# COASTING parameter
deltat = 2 * 24 * 3600 / TU
# Plot functions
function plot_trajNV_multiarc_multidyn_withcoasting_1arc(sol, nb_arcs, tvec, moon_arcs, uncontrolled_arcs)
sol_time = sol.time_grid.value
Nstate = length(sol.state.value(sol.time_grid.value[1]))
Nsol = length(sol_time)
sol_state = zeros(Nstate * nb_arcs, Nsol)
sol_control = zeros(3 * (nb_arcs - length(uncontrolled_arcs)), Nsol)
# sol_control = zeros(3 * nb_arcs, Nsol)
# k = 1
for i in range(1, Nsol)
sol_state[:, i] = sol.state.value(sol.time_grid.value[i])
sol_control[:, i] = sol.control.value(sol.time_grid.value[i])
# if i ∉ uncontrolled_arcs
# k += 1
# end
end
for m in moon_arcs
for i in range(1, Nsol)
Nbegin = 1 + Nstate * (m - 1)
Nend = 7 + Nstate * (m - 1)
sol_state[Nbegin : Nend, i] = moon2emb(phi(sol_time[i], tvec[m], tvec[m+1]), sol_state[Nbegin : Nend, i])
end
end
x_vals_opti = zeros(nb_arcs, Nsol)
y_vals_opti = zeros(nb_arcs, Nsol)
z_vals_opti = zeros(nb_arcs, Nsol)
vx_vals_opti = zeros(nb_arcs, Nsol)
vy_vals_opti = zeros(nb_arcs, Nsol)
vz_vals_opti = zeros(nb_arcs, Nsol)
m_vals_opti = zeros(nb_arcs, Nsol)
ux_vals_opti = zeros(nb_arcs, Nsol)
uy_vals_opti = zeros(nb_arcs, Nsol)
uz_vals_opti = zeros(nb_arcs, Nsol)
u_norm = zeros(nb_arcs, Nsol)
k = 1
for i in range(1, nb_arcs)
x_vals_opti[i, :] = sol_state[1 + Nstate * (i - 1), :]
y_vals_opti[i, :] = sol_state[2 + Nstate * (i - 1), :]
z_vals_opti[i, :] = sol_state[3 + Nstate * (i - 1), :]
vx_vals_opti[i, :] = sol_state[4 + Nstate * (i - 1), :]
vy_vals_opti[i, :] = sol_state[5 + Nstate * (i - 1), :]
vz_vals_opti[i, :] = sol_state[6 + Nstate * (i - 1), :]
m_vals_opti[i, :] = sol_state[7 + Nstate * (i - 1), :]
if i ∉ uncontrolled_arcs
ux_vals_opti[i, :] = sol_control[1 + 3 * (k - 1), :]
uy_vals_opti[i, :] = sol_control[2 + 3 * (k - 1), :]
uz_vals_opti[i, :] = sol_control[3 + 3 * (k - 1), :]
u_norm[i, :] = (ux_vals_opti[i, :].^2 + uy_vals_opti[i, :].^2 + uz_vals_opti[i, :].^2).^(1/2)
k += 1
end
end
sol_time_plot = LinRange(tvec[1], tvec[end], N)
x_moon_pos = [x_moon(t) for t in sol_time_plot]
y_moon_pos = [y_moon(t) for t in sol_time_plot]
z_moon_pos = [z_moon(t) for t in sol_time_plot]
x_earth_pos = [x_earth(t) for t in sol_time_plot]
y_earth_pos = [y_earth(t) for t in sol_time_plot]
z_earth_pos = [z_earth(t) for t in sol_time_plot]
p = plot(x_moon_pos, y_moon_pos, z_moon_pos, label = "moon orbit")
plot!(x_earth_pos, y_earth_pos, z_earth_pos, label = "earth orbit")
scatter!([x_vals_opti[1, 1]], [y_vals_opti[1, 1]], [z_vals_opti[1, 1]], label = "previous occultation", color = :blue)
labels = ["next occultation"]
for i in range(1, nb_arcs)
rand_color = RGB(rand(), rand(), rand())
plot!(x_vals_opti[i, :], y_vals_opti[i, :], z_vals_opti[i, :], size=(600, 600), camera = (10,30), xlabel="x", ylabel="y", label = false, zlabel="z", linewidth = 2, color = "black", legend =:topleft)
scatter!([x_vals_opti[i, end]], [y_vals_opti[i, end]], [z_vals_opti[i, end]], label = labels[i], color = :red)
arrow_factor = 1e-1
inds = findall(u_norm[i, :] .> 0.001)[1:2:end]
quiver!(x_vals_opti[i, inds], y_vals_opti[i, inds], z_vals_opti[i, inds], quiver=(ux_vals_opti[i, inds] * arrow_factor, uy_vals_opti[i, inds] * arrow_factor, uz_vals_opti[i, inds] * arrow_factor), label="thrust directions", arrow=true, color = "red")
# if i ∉ uncontrolled_arcs
# arrow_factor = 1e-1
# inds = findall(u_norm[k, :] .> 0.01)[1:2:end]
# quiver!(x_vals_opti[i, inds], y_vals_opti[i, inds], z_vals_opti[i, inds], quiver=(ux_vals_opti[k, inds] * arrow_factor, uy_vals_opti[k, inds] * arrow_factor, uz_vals_opti[k, inds] * arrow_factor), label="thrust directions", arrow=true, color = "red")
# k += 1
# end
end
xlims!(-2, 2)
ylims!(-2, 2)
zlims!(-2, 2)
display(p)
end
function plot_trajNV_multiarc_multidyn_synodic_1arc(sol, nb_arcs, tvec, moon_arcs)
sol_time = sol.time_grid.value
Nstate = length(sol.state.value(sol.time_grid.value[1]))
Nsol = length(sol_time)
sol_state = zeros(Nstate * nb_arcs, Nsol)
for i in range(1, Nsol)
sol_state[:, i] = sol.state.value(sol.time_grid.value[i])
end
for m in moon_arcs
for i in range(1, Nsol)
Nbegin = 1 + Nstate * (m - 1)
Nend = Nstate + Nstate * (m - 1)
sol_state[Nbegin : Nend, i] = moon2emb(sol_time[i], sol_state[Nbegin : Nend, i])
end
end
x_vals_opti = zeros(Nsol)
y_vals_opti = zeros(Nsol)
z_vals_opti = zeros(Nsol)
vx_vals_opti = zeros(Nsol)
vy_vals_opti = zeros(Nsol)
vz_vals_opti = zeros(Nsol)
m_vals_opti = zeros(Nsol)
for i in range(1, nb_arcs)
x_vals_opti = sol_state[1 , :]
y_vals_opti = sol_state[2 , :]
z_vals_opti = sol_state[3 , :]
vx_vals_opti = sol_state[4 , :]
vy_vals_opti = sol_state[5 , :]
vz_vals_opti = sol_state[6 , :]
m_vals_opti = sol_state[7 , :]
end
x_syn = zeros( Nsol)
y_syn = zeros(Nsol)
z_syn = zeros( Nsol)
for ii = 1:Nsol
x_sol_syn = ECLIPJ2000toSynodic(sol_time[ii] * TU,
sol_state[1 : 3, ii])
x_syn[ii] = x_sol_syn[1]
y_syn[ii] = x_sol_syn[2]
z_syn[ii] = x_sol_syn[3]
end
p = plot(x_syn, y_syn, z_syn, legend = false, linewidth = 2, color = :black)
scatter!([x_syn[end]], [y_syn[end]], [z_syn[end]], color = :red, xlabel = "x", ylabel = "y", zlabel = "z")
scatter!([x_syn[1]], [y_syn[1]], [z_syn[1]], color = :red, xlabel = "x", ylabel = "y", zlabel = "z")
scatter!([norm([x_moon(t0), y_moon(t0), z_moon(t0)])], [0], [0], color = :grey, label = "moon", markersize=7)
scatter!([norm([x_earth(t0), y_earth(t0), z_earth(t0)])], [0], [0], color = :blue, label = "earth", markersize=10)
xlims!(-2, 2)
ylims!(-2, 2)
zlims!(-2, 2)
display(p)
end
function ECLIPJ2000toSynodic(et, x)
xm = spkezr("MOON", et, "ECLIPJ2000", "NONE", "EARTH")
r = xm[1][1:3]
v = xm[1][4:6]
normr = norm(r)
h = cross(r, v)
normh = norm(h)
er = r/normr
eh = h/normh
et = cross(eh, er)/norm(cross(eh, er))
IS = [er[1] er[2] er[3];
et[1] et[2] et[3];
eh[1] eh[2] eh[3]]
xs = IS * x[1:3]
return xs
end
# Dynamics functions
function propagate!(du, u, p, t)
r = u[1:3]
v = u[4:6]
m = u[7] * mass_scaling_factor
x_e = [x_earth(t), y_earth(t), z_earth(t)]
x_m = [x_moon(t), y_moon(t), z_moon(t)]
x_s = [x_sun(t), y_sun(t), z_sun(t)]
normrE = sqrt(sum((x_e - r).^2))
normrM = sqrt(sum((x_m - r).^2))
normrS = sqrt(sum((x_s - r).^2))
normrSE = sqrt(sum((x_e - x_s).^2))
normrMS = sqrt(sum((x_m - x_s).^2))
dv = mu_Earth / normrE^3 * (x_e - r) + mu_Moon / normrM^3 * (x_m - r) + mu_Sun / normrS^3 * (x_s - r) - (1 / (mass_earth + mass_moon)) * ( x_s * (mu_Sun * mass_earth / normrSE^3 + mu_Moon * mass_sun / normrMS^3) - x_m * (mu_Moon * mass_sun / normrMS^3) - x_e * (mu_Sun * mass_earth / normrSE^3))
dvu = Tmax * p / m
dm = - Q * sqrt(sum(p.^2)) / mass_scaling_factor
du[1:3] = v
du[4:6] = dv + dvu
du[7] = dm
end
function F0(t, x, u)
# Earth & Moon & Sun gravity
r = x[1:3]
v = x[4:6]
m = x[7] * mass_scaling_factor
N_th = x[8]
x_e = [x_earth(t), y_earth(t), z_earth(t)]
x_m = [x_moon(t), y_moon(t), z_moon(t)]
x_s = [x_sun(t), y_sun(t), z_sun(t)]
normrE = sqrt(sum((x_e - r).^2))
normrM = sqrt(sum((x_m - r).^2))
normrS = sqrt(sum((x_s - r).^2))
normrSE = sqrt(sum((x_e - x_s).^2))
normrMS = sqrt(sum((x_m - x_s).^2))
dv = mu_Earth / normrE^3 * (x_e - r) + mu_Moon / normrM^3 * (x_m - r) + mu_Sun / normrS^3 * (x_s - r) - (1 / (mass_earth + mass_moon)) * ( x_s * (mu_Sun * mass_earth / normrSE^3 + mu_Moon * mass_sun / normrMS^3) - x_m * (mu_Moon * mass_sun / normrMS^3) - x_e * (mu_Sun * mass_earth / normrSE^3))
dvu = N_th * Tmax * u / m
dm = - N_th * Q * sqrt(sum(u.^2)) / mass_scaling_factor
dx = [v; dv + dvu; dm; 0]
return dx
end
function Fu(t, x, u)
# Earth & Moon & Sun gravity
r = x[1:3]
v = x[4:6]
m = x[7] * mass_scaling_factor
N_th = x[8]
x_e = [x_earth(t), y_earth(t), z_earth(t)]
x_m = [x_moon(t), y_moon(t), z_moon(t)]
x_s = [x_sun(t), y_sun(t), z_sun(t)]
normrE = sqrt(sum((x_e - r).^2))
normrM = sqrt(sum((x_m - r).^2))
normrS = sqrt(sum((x_s - r).^2))
normrSE = sqrt(sum((x_e - x_s).^2))
normrMS = sqrt(sum((x_m - x_s).^2))
dvg = mu_Earth / normrE^3 * (x_e - r) + mu_Moon / normrM^3 * (x_m - r) + mu_Sun / normrS^3 * (x_s - r) - (1 / (mass_earth + mass_moon)) * ( x_s * (mu_Sun * mass_earth / normrSE^3 + mu_Moon * mass_sun / normrMS^3) - x_m * (mu_Moon * mass_sun / normrMS^3) - x_e * (mu_Sun * mass_earth / normrSE^3))
dvu = N_th * Tmax * u / m
dv = dvg + dvu
dm = - N_th * Q * sqrt(sum(u.^2)) / mass_scaling_factor
dx = [ v; dv; dm; 0 ]
return dx
end
t0_J200 = 1.107747244e9
tf_J200 = 1.110817407e9
N = 50000
t_values = LinRange(t0_J200, tf_J200, N-3)
t_values = vcat(-5e9, 0.0, collect(t_values), tf_J200 * 5)
states_moon = zeros(6, N)
states_earth = zeros(6, N)
states_sun = zeros(6, N)
states_moon_wrt_sun = zeros(6, N)
states_earth_wrt_moon = zeros(6, N)
t0 = t0_J200 / TU
tf = tf_J200 / TU
for i = 1:N
states_moon[:,i], _ = spkezr("MOON", t_values[i], "ECLIPJ2000", "NONE", "EARTH MOON BARYCENTER")
states_earth[:,i], _ = spkezr("EARTH", t_values[i], "ECLIPJ2000", "NONE", "EARTH MOON BARYCENTER")
states_sun[:,i], _ = spkezr("SUN", t_values[i], "ECLIPJ2000", "NONE", "EARTH MOON BARYCENTER")
states_moon_wrt_sun[:,i], _ = spkezr("MOON", t_values[i], "ECLIPJ2000", "NONE", "SUN")
states_earth_wrt_moon[:,i], _ = spkezr("EARTH", t_values[i], "ECLIPJ2000", "NONE", "MOON")
end
x_moon = DataInterpolations.LinearInterpolation(states_moon[1,:] / LU, t_values / TU)
y_moon = DataInterpolations.LinearInterpolation(states_moon[2,:] / LU, t_values / TU)
z_moon = DataInterpolations.LinearInterpolation(states_moon[3,:] / LU, t_values / TU)
vx_moon = DataInterpolations.LinearInterpolation(states_moon[4,:] / LU * TU, t_values / TU)
vy_moon = DataInterpolations.LinearInterpolation(states_moon[5,:] / LU * TU, t_values / TU)
vz_moon = DataInterpolations.LinearInterpolation(states_moon[6,:] / LU * TU, t_values / TU)
x_earth = DataInterpolations.LinearInterpolation(states_earth[1,:] / LU, t_values / TU)
y_earth = DataInterpolations.LinearInterpolation(states_earth[2,:] / LU, t_values / TU)
z_earth = DataInterpolations.LinearInterpolation(states_earth[3,:] / LU, t_values / TU)
vx_earth = DataInterpolations.LinearInterpolation(states_earth[4,:] / LU * TU, t_values / TU)
vy_earth = DataInterpolations.LinearInterpolation(states_earth[5,:] / LU * TU, t_values / TU)
vz_earth = DataInterpolations.LinearInterpolation(states_earth[6,:] / LU * TU, t_values / TU)
x_sun = DataInterpolations.LinearInterpolation(states_sun[1,:] / LU, t_values / TU)
y_sun = DataInterpolations.LinearInterpolation(states_sun[2,:] / LU, t_values / TU)
z_sun = DataInterpolations.LinearInterpolation(states_sun[3,:] / LU, t_values / TU)
x_earth_wrt_moon = DataInterpolations.LinearInterpolation(states_earth_wrt_moon[1,:] / LU, t_values / TU)
y_earth_wrt_moon = DataInterpolations.LinearInterpolation(states_earth_wrt_moon[2,:] / LU, t_values / TU)
z_earth_wrt_moon = DataInterpolations.LinearInterpolation(states_earth_wrt_moon[3,:] / LU, t_values / TU)
x_moon_wrt_sun = DataInterpolations.LinearInterpolation(states_moon_wrt_sun[1,:] / LU, t_values / TU)
y_moon_wrt_sun = DataInterpolations.LinearInterpolation(states_moon_wrt_sun[2,:] / LU, t_values / TU)
z_moon_wrt_sun = DataInterpolations.LinearInterpolation(states_moon_wrt_sun[3,:] / LU, t_values / TU)
t1_J200 = 1.10829103e9
t1_moon, _ = spkezr("MOON", t1_J200, "ECLIPJ2000", "NONE", "EARTH MOON BARYCENTER")
t1 = t1_J200 / TU
occult1 = zeros(6)
occult1_ECI = [-297664.1158..., 212871.4885..., -76.96308643..., 1.453863208..., -1.136754567..., -0.032783807...]
occult1[1:3] = (occult1_ECI[1:3] + t1_moon[1:3]) / LU
occult1[4:6] = (occult1_ECI[4:6] + t1_moon[4:6]) / LU * TU
t6_J200 = 1.110817407e9
t6_moon, _ = spkezr("MOON", t6_J200, "ECLIPJ2000", "NONE", "EARTH MOON BARYCENTER")
t6 = t6_J200 / TU
occult6 = zeros(6)
occult6_ECI = [-365732.5404..., 39738.61049..., -83.77279923..., 1.854101596..., -0.310457164..., 0.010142901...]
occult6[1:3] = (occult6_ECI[1:3] + t6_moon[1:3]) / LU
occult6[4:6] = (occult6_ECI[4:6] + t6_moon[4:6]) / LU * TU
@def ocp begin
t ∈ [ t1, t6 ], time
x ∈ R^8, state
u ∈ R³, control
thrust = x[8]
mass = x[7]
-10 ≤ x₁(t) ≤ 10
-10 ≤ x₂(t) ≤ 10
-10 ≤ x₃(t) ≤ 10
-10 ≤ x₄(t) ≤ 10
-10 ≤ x₅(t) ≤ 10
-10 ≤ x₆(t) ≤ 10
0 ≤ x₇(t) ≤ 1 # careful here ! dry mass > 0 && dry_mass ≤ x₇(t) ≤ dry_mass + fuel_mass
1e-5 ≤ x₈(t) ≤ 50
0 ≤ sum(u(t).^2) ≤ 1
x[1:6](t1) == occult1
x₇(t1) == mass_init
x[1:6](t6) == occult6
ẋ(t) == Fu(t, x(t), u(t))
x₈(t6) → min
end
# Works but is slower:
# sol = solve(ocp, grid_size = 100, max_iter = 100, tol = 1e-6, acceptable_tol = 1e-5, disc_method=:gauss_legendre_2)
# Creating initial guess
ppr = 1e-16 * ones(3)
x0 = [occult1..., 1..., 1..., ]
tspan = (t1, t6)
time_points = LinRange(t1, t6, 500)
prob = ODEProblem(propagate!, x0, tspan, ppr)
solpr = solve(prob, Tsit5(), saveat=time_points)
Nsolu = length(solpr.u)
plot([solpr.u[i][1] for i in range(1, Nsolu)], [solpr.u[i][2] for i in range(1, Nsolu)], [solpr.u[i][3] for i in range(1, Nsolu)])
xlims!(-2, 2)
ylims!(-2, 2)
zlims!(-2, 2)
sol = solve(ocp,
init = (time=solpr.t, state=solpr.u, control=ppr),
grid_size = 100, max_iter = 1000, tol = 1e-6, acceptable_tol = 1e-5,
disc_method=:gauss_legendre_2)
initial_guess = sol
sol = solve(ocp, init = initial_guess,
grid_size = 150, max_iter = 1000, tol = 1e-6, disc_method=:gauss_legendre_2)
time_intervals = [t1, t6]
plot(sol,size = (600,1500))
control_matrix = zeros(3, length(sol.time_grid.value))
for i in range(1, length(sol.time_grid.value))
control_matrix[:,i] = sol.control.value(sol.time_grid.value[i])
end
control_norm = [norm(col) for col in eachcol(control_matrix)]
plot(sol.time_grid.value, control_norm, linewidth = 2, label = false)
ylims!(0,1)
moon_arcs = []
uncontrolled_arcs = []
plot_trajNV_multiarc_multidyn_withcoasting_1arc(sol, 1, time_intervals, moon_arcs, uncontrolled_arcs)
plot_trajNV_multiarc_multidyn_synodic_1arc(sol, 1, time_intervals, moon_arcs)
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Documentation: sign conventions (min/max, p⁰, constraints, duals) and how they appear in a solutionPosiblemente ocupada @ocots la tomó hace 18 días. Abiertodocumentation
control-toolbox/OptimalControl.jl#1015 · 2 comentarios · 1 asignado ·
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