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Still not working. Up to the loop though.

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This commit is contained in:
Connor
2021-09-01 11:08:43 -06:00
parent 5daf007e5b
commit 58ad3c5293
3 changed files with 59 additions and 94 deletions
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3
julia/src/conversions.jl
View File

@@ -69,6 +69,9 @@ function xyz_to_oe(cart_vec::Vector,μ::Real)
end
"""
Converts a series of thrust vectors from R,Θ,H frame to cartesian
"""
function conv_T(Tr::Vector{Float64},
TΘ::Vector{Float64},
Th::Vector{Float64},

129
julia/src/find_closest.jl
View File

@@ -2,39 +2,6 @@ using JuMP, Ipopt
export nlp_solve
function treat_inputs(x::Vector{T}) where T <: Real
thrust = T[]
α = T[]
β = T[]
n::Int = length(x)
for i in 1:n
if i % 3 == 1
push!(thrust,x[i])
elseif i % 3 == 2
push!(α,x[i])
else
push!(β,x[i])
end
end
hcat(thrust, α, β)
end
function treat_inputs(x::NTuple{90,T}) where T <: Real
thrust = T[]
α = T[]
β = T[]
for i in 1:90
if i % 3 == 1
push!(thrust,x[i])
elseif i % 3 == 2
push!(α,x[i])
else
push!(β,x[i])
end
end
hcat(thrust, α, β)
end
function nlp_solve(start::Vector{Float64},
final::Vector{Float64},
craft::Sc,
@@ -43,7 +10,8 @@ function nlp_solve(start::Vector{Float64},
tf::Float64,
Txi::Vector{Float64},
Tyi::Vector{Float64},
Tzi::Vector{Float64},
Tzi::Vector{Float64};
solver_options=(),
tol=1e-6)
n::Int = length(Txi)
@@ -53,69 +21,58 @@ function nlp_solve(start::Vector{Float64},
throw("Bad number of Tzs")
end
model = Model(Ipopt.Optimizer)
set_optimizer_attribute(model, "max_cpu_time", 30.)
# First propagate the initial guess
path, masses, final_state = prop(hcat(Txi, Tyi, Tzi),
start,
craft,
μ,
tf-t0)
@assert final ≈ final_state
model = Model(optimizer_with_attributes(Ipopt.Optimizer, solver_options...))
@variables(model, begin
Tx[i=1:n], (start=Txi[i])
Ty[i=1:n], (start=Tyi[i])
Tz[i=1:n], (start=Tzi[i])
x[1:n]
y[1:n]
z[1:n]
dx[1:n]
dy[1:n]
dz[1:n]
mass[1:n]
x[i=1:n], (start=path[1][i])
y[i=1:n], (start=path[2][i])
z[i=1:n], (start=path[3][i])
dx[i=1:n], (start=path[4][i])
dy[i=1:n], (start=path[5][i])
dz[i=1:n], (start=path[6][i])
mass[i=1:n], (start=masses[i])
end)
@constraints(model,begin
x[1] == start[1]
y[1] == start[2]
z[1] == start[3]
dx[1] == start[4]
dy[1] == start[5]
dz[1] == start[6]
mass[1] == craft.mass
x[n] == final[1]
y[n] == final[2]
z[n] == final[3]
dx[n] == final[4]
dy[n] == final[5]
dz[n] == final[6]
end)
# Fix initial conditions
fix(x[1], start[1], force = true)
fix(y[1], start[2], force = true)
fix(z[1], start[3], force = true)
fix(dx[1], start[4], force = true)
fix(dy[1], start[5], force = true)
fix(dz[1], start[6], force = true)
fix(mass[1], craft.mass, force = true)
register(model, :prop_one_simple, 11, prop_one_simple; autodiff = true)
@NLexpression(model, )
# Fix final conditions
fix(x[n], final[1], force = true)
fix(y[n], final[2], force = true)
fix(z[n], final[3], force = true)
fix(dx[n], final[4], force = true)
fix(dy[n], final[5], force = true)
fix(dz[n], final[6], force = true)
# @NLexpression()
@NLexpression(model, r_mag[i = 1:n], sqrt(x[i]^2 + y[i]^2 + z[i]^2))
@NLexpression(model, v_mag[i = 1:n], sqrt(dx[i]^2 + dy[i]^2 + dz[i]^2))
@NLexpression(model, σ0[i = 1:n], (x[i]*dx[i] + y[i]*dy[i] + z[i]*dz[i])/sqrt(μ))
@NLexpression(model, a[i = 1:n], 1/(2/r_mag[i] - v_mag[i]^2/μ))
# Elliptical Specific
@NLexpression(model, ΔM_ell[i = 1:n], sqrt(μ) / sqrt(a[i]^3) * (tf-t0)/(2n))
# Parabolic/Hyperbolic Specific
@NLexpression(model, ΔN_hyp[i = 1:n], sqrt(μ) / sqrt(-a[i]^3) * (tf-t0)/(2n))
for i in 2:n
@NLconstraint(model, x[i] == sqrt(x[i-1]^2))
# @NLconstraint(model, x[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[1])
# @NLconstraint(model, y[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[2])
# @NLconstraint(model, z[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[3])
# @NLconstraint(model, dx[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[4])
# @NLconstraint(model, dy[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[5])
# @NLconstraint(model, dz[i] == prop_one_simple(Tx[i-1], Ty[i-1], Tz[i-1],
# x[i-1], y[i-1], z[i-1],
# dx[i-1], dy[i-1], dz[i-1],
# (tf-t0)/n, μ)[6])
@NLconstraint(model, x[i] == a[i-1])
@NLconstraint(model, mass[i] == mass[i-1] - craft.mass_flow_rate*√(Tx[i-1]^2 +
Ty[i-1]^2 +
Tz[i-1]^2)*(tf-t0)/n)

19
julia/test/find_closest.jl
View File

@@ -1,7 +1,6 @@
@testset "Find Closest" begin
using JuMP
using Thesis: treat_inputs
# Initial Setup
sc = Sc("test")
@@ -14,12 +13,17 @@
# A simple orbit raising
start = oe_to_xyz([ a, e, i, 0., 0., 0. ], μs["Earth"])
ΔVs = repeat([0.6, 0., 0.]', outer=(n,1))
final = prop(ΔVs, start, sc, μs["Earth"], prop_time)[3]
Tx, Ty, Tz = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
start,
sc.mass,
sc,
prop_time,
μs["Earth"])
final = prop(hcat(Tx, Ty, Tz), start, sc, μs["Earth"], prop_time)[3]
new_T = 2π*√(xyz_to_oe(final, μs["Earth"])[1]^3/μs["Earth"])
# This should be close enough to 0.6
Tr, TΘ, Th = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
Tx, Ty, Tz = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
start,
sc.mass,
sc,
@@ -31,9 +35,10 @@
μs["Earth"],
0.0,
prop_time,
Tr,
TΘ,
Th)
Tx,
Ty,
Tz)
# solver_options=("max_cpu_time" => 30.))
# Test and plot
@test JuMP.termination_status(result) == MOI.OPTIMAL