Fully working mbh for two phase missions!
This commit is contained in:
Connor
@@ -5,41 +5,22 @@ Generates pareto-distributed random numbers
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This is usually around one to two percent, but sometimes up to ten or so (fat tails)
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"""
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function pareto(shape::Tuple{Int, Int}, α::Float64=1.01)
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s = rand((-1,1), shape)
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r = rand(Float64, shape)
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function pareto(shape::Union{Tuple{Int, Int}, Int, Nothing}=nothing; α::Float64=1.01)
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if shape !== nothing
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s = rand((-1,1), shape)
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r = rand(Float64, shape)
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else
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s = rand((-1,1))
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r = rand(Float64)
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end
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ϵ = 1e-10
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return 1 .+ (s./ϵ) * (α - 1.0) ./ (ϵ ./ (ϵ .+ r)).^(-α)
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end
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function pareto(shape::Int, α::Float64=1.01)
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s = rand((-1,1), shape)
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r = rand(Float64, shape)
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ϵ = 1e-10
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return 1 .+ (s./ϵ) * (α - 1.0) ./ (ϵ ./ (ϵ .+ r)).^(-α)
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end
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function pareto(α::Float64=1.01)
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s = rand((-1,1))
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r = rand(Float64)
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ϵ = 1e-10
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return 1 + (s./ϵ) * (α - 1.0) ./ (ϵ ./ (ϵ .+ r)).^(-α)
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end
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function pareto_add(α::Float64=1.01)
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s = rand((-1,1))
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r = rand(Float64)
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ϵ = 1e-10
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return (s./ϵ) * (α - 1.0) ./ (ϵ ./ (ϵ .+ r)).^(-α)
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end
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"""
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Returns a random date between two dates
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"""
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function gen_date(date_range::Tuple{DateTime, DateTime})
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l0, lf = date_range
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l0 + Millisecond(floor(rand()*(lf-l0).value))
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end
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Base.rand(l0::DateTime,lf::DateTime) = l0 + Millisecond(floor(rand()*(lf-l0).value))
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"""
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Perturbs a valid mission with pareto-distributed variables, generating a mission guess
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@@ -47,7 +28,7 @@ Perturbs a valid mission with pareto-distributed variables, generating a mission
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function perturb(mission::Mission)
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mission_guess = Bad_Mission("Starting point")
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while typeof(mission_guess) == Bad_Mission
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new_launch_date = mission.launch_date + Dates.Second(floor(7day * pareto_add()))
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new_launch_date = mission.launch_date + Dates.Second(floor(7day * (pareto()-1)))
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new_launch_v∞ = mission.launch_v∞ .* pareto(3)
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new_phases = Vector{Phase}()
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for phase in mission.phases
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@@ -58,16 +39,7 @@ function perturb(mission::Mission)
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new_thrust_profile = phase.thrust_profile .* pareto(size(phase.thrust_profile))
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push!(new_phases, Phase(phase.planet, new_v∞_in, new_v∞_out, new_tof, new_thrust_profile))
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end
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# TODO: Mission_Guess.validate()
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try
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mission_guess = Mission_Guess(mission.sc, mission.start_mass, new_launch_date, new_launch_v∞, new_phases)
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catch e
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if isa(e, Mass_Error) ||isa(e,V∞_Error) || isa(e,HitPlanet_Error)
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continue
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else
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rethrow()
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end
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end
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mission_guess = Mission_Guess(mission.sc, mission.start_mass, new_launch_date, new_launch_v∞, new_phases)
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end
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return mission_guess
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end
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@@ -89,7 +61,7 @@ function mission_guess( flybys::Vector{Body},
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n = 20
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# Determine the launch conditions
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launch_date = gen_date(launch_window)
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launch_date = rand(launch_window...)
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launch_v∞_normalized = rand(-1:0.0001:1, 3)
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launch_v∞ = rand(0:0.0001:√max_C3_out) * launch_v∞_normalized/norm(launch_v∞_normalized)
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@@ -142,52 +114,6 @@ function mission_guess( flybys::Vector{Body},
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return mission_guess
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end
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"""
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Sequentially calls the NLP solver to attempt to solve based on the initial guess
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"""
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function inner_loop_solve(guess::Mission_Guess)
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v∞_out = guess.launch_v∞
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mass = guess.start_mass
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current_planet = Earth
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time = utc2et(Dates.format(guess.launch_date,"yyyy-mm-ddTHH:MM:SS"))
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start = state(current_planet, time, v∞_out, mass)
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corrected_phases = Vector{Phase}()
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for i in 1:length(guess.phases)
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phase = guess.phases[i]
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current_planet = phase.planet
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time += phase.tof
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goal = state(current_planet, time, phase.v∞_in)
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result = solve_phase( start, goal, guess.sc, phase.tof, phase.thrust_profile)
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result.converged || return Bad_Mission(result.info) # Drop if it's not working
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corrected_phase = Phase(phase.planet, phase.v∞_in, phase.v∞_out, phase.tof, result.sol)
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push!(corrected_phases, corrected_phase)
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mass_used = mass_consumption(guess.sc, corrected_phase)
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mass -= mass_used
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if i != length(guess.phases)
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v∞_out = phase.v∞_out
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start = state(current_planet, time, v∞_out, mass)
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end
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end
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return Mission(guess.sc, guess.start_mass, guess.launch_date, guess.launch_v∞, corrected_phases)
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end
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"""
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The cost function for the mission
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TODO: This will probably move and eventually be passed as an argument
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"""
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function cost(mission::Mission, max_C3::Float64, max_v∞::Float64)
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mass_used = 0.0
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for phase in mission.phases mass_used += mass_used(sc, phase) end
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mass_percent = mass_used/mission.sc.dry_mass
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C3_percent = ( mission.launch_v∞ ⋅ mission.launch_v∞ ) / max_C3
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v∞_percent = norm(mission.phases[end].v∞_in) / max_v∞
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return 3mass_percent + C3_percent + v∞_percent
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end
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cost(_::Bad_Mission) = Inf
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"""
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This is the main monotonic basin hopping function. There's a lot going on here, but the general idea
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is that hopefully you can provide mission parameters and a list of flybys and get the optimal
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@@ -200,44 +126,50 @@ function mbh( flybys::Vector{Body},
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max_C3::Float64,
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max_v∞::Float64,
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latest_arrival::DateTime,
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cost_fn::Function,
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primary::Body=Sun;
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search_patience::Int=10_000,
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drill_patience::Int=50,
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verbose::Bool=false)
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# A convenience function
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# Convenience Functions
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random_guess() = mission_guess(flybys,sc,start_mass,launch_window,max_C3,max_v∞,latest_arrival,primary)
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cost(m::Mission) = cost(m, max_C3, max_v∞)
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status(s,d,l) = print("\r\t", "search: ", s, " drill: ", d, " archive length: ", l, " ")
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solve(g::Mission_Guess) = solve_mission(g, launch_window, latest_arrival)
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cost(m::Mission) = cost_fn(m, max_C3, max_v∞)
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cost(_::Nothing) = Inf
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# Initialize stuff
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search_count = 0
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x_current = Bad_Mission("Starting point")
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drill_count = 0
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archive = Vector{Mission}()
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function log()
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print("\r ")
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print("\rsearch: $(search_count) drill: $(drill_count) archive: $(length(archive))\t")
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end
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# The main loop
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x_current = nothing
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if verbose println("Starting Monotonic Basin Hopper") end
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while search_count < search_patience
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# Intialize an x_star, if it doesn't converge, hop on to the next basin
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search_count += 1
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drill_count = 0
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if verbose status(search_count, drill_count, length(archive)) end
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x_star = inner_loop_solve(random_guess())
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verbose && log()
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x_star = solve(random_guess())
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x_star.converged || continue
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x_basin = x_star
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# If it does, though, we check to see if it's better than the current
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if cost(x_star) < cost(x_current) x_current = x_star end
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# Either way, we need to drill into this particular basin, since it's valid
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while drill_count < drill_patience
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if verbose status(search_count, drill_count, length(archive)) end
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verbose && log()
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#Perturb to generate a slightly different x_star
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x_star = inner_loop_solve(perturb(x_basin))
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x_star = solve(perturb(x_basin))
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# If better than the best, then keep it as current
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if x_star.converged && cost(x_star) < cost(x_current)
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@@ -258,6 +190,8 @@ function mbh( flybys::Vector{Body},
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end
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if verbose println() end
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return x_current, archive
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end
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@@ -31,7 +31,7 @@ NOTE: This function will output a proper mission if it succeeded and just re-ret
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guess otherwise
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"""
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function solve_mission( guess::Mission_Guess,
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launch_window::Vector{DateTime},
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launch_window::Tuple{DateTime,DateTime},
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latest_arrival::DateTime;
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tol=1e-10,
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verbose::Bool=false,
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@@ -114,7 +114,7 @@ function solve_mission( guess::Mission_Guess,
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else
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g = zeros(num_constraints)
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optimizer!(g,x)
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println(g)
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if verbose println(g) end
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return guess
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end
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@@ -21,9 +21,6 @@ function prop_one(ΔV_unit::Vector{<:Real},
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time::Float64,
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primary::Body=Sun)
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for direction in ΔV_unit
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abs(direction) <= 1.0 || throw(PropOne_Error(ΔV_unit))
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end
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ΔV = max_ΔV(craft.duty_cycle, craft.num_thrusters, craft.max_thrust, time, 0., state[7]) * ΔV_unit
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halfway = laguerre_conway(state, time/2, primary) + [zeros(3); ΔV]
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final = laguerre_conway(halfway, time/2, primary)
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@@ -81,3 +78,24 @@ end
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Convenience function for propagating a state with no thrust
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"""
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prop(x::Vector{Float64}, t::Float64, p::Body=Sun) = prop(zeros(1000,3), [x;1.], no_thrust, t, p)[1]
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"""
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This is solely for the purposes of getting the final state of a mission or guess
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"""
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function prop(m::Mission)
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time = m.launch_date
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current_planet = Earth
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start = state(current_planet, time, m.launch_v∞, m.start_mass)
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final = zeros(7)
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for phase in m.phases
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final = prop(phase.thrust_profile, start, m.sc, phase.tof)[2]
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mass = final[7]
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current_planet = phase.planet
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time += Dates.Second(floor(phase.tof))
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start = state(current_planet, time, phase.v∞_out, mass)
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end
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return final
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end
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