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Add autotune_nomad.jl
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‎Project.toml‎

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@@ -8,6 +8,7 @@ DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
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KiteUtils = "90980105-b163-44e5-ba9f-8b1c83bb0533"
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
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NOMAD = "02130f1c-4665-5b79-af82-ff1385104aa0"
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Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
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Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
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StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
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KiteUtils = "0.10.7"
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LinearAlgebra = "1.10, 1.11"
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NLsolve = "4.5.1"
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NOMAD = "2.4.1"
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PRIMA = "0.2.2"
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Parameters = "0.12.3"
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Pkg = "1.10, 1.11"

‎scripts/autotune_nomad.jl‎

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# this script tunes the controller parameters (well, seven of them)
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# TODO: make sure that calling autotune does not make the performance worse
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# DONE: add the mean square of the acceleration to the damage metric
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using Pkg
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if ! ("ControlPlots" ∈ keys(Pkg.project().dependencies))
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using TestEnv; TestEnv.activate()
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using Test
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end
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using WinchControllers, KiteUtils, PRIMA, NOMAD, ControlPlots
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TUNED::Bool = false
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load_settings("system.yaml")
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function calc_force(v_wind, v_ro)
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(v_wind - v_ro)^2 * 4000.0 / 16.0
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end
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function plot(lg::WCLogger)
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p1=plotx(lg.time, lg.v_wind, [lg.v_ro, lg.v_set_in], lg.f_err*0.001, lg.v_err, lg.acc, lg.force*0.001, lg.state,
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title="Winch controller test, all controllers active",
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ylabels=["v_wind [m/s]", "v_reel_out [m/s]", "f_err [kN]", "v_error [m/s]", "acc [m/s²]", "force [kN]", "state"],
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ysize=10,
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labels=["v_wind", ["v_reel_out", "v_set_in"]],
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fig="test_winchcontroller",)
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display(p1)
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end
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function simulate(wcs::WCSettings; return_lg::Bool = false)
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if TUNED
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set = load_settings("system_tuned.yaml")
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else
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set = load_settings("system.yaml")
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end
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# define the simulation parameters
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DURATION = 10.0
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V_WIND_MAX = 9.0 # max wind speed of test wind
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V_WIND_MIN = 0.0 # min wind speed of test wind
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FREQ_WIND = 0.25 # frequency of the triangle wind speed signal
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# create the logger
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lg::WCLogger = WCLogger(DURATION, wcs.dt, set.max_force, wcs.max_acc, wcs.damage_factor)
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STARTUP = get_startup(wcs, length(lg))
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V_WIND = STARTUP .* get_triangle_wind(wcs, V_WIND_MIN, V_WIND_MAX, FREQ_WIND, length(lg))
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# create and initialize winch controller
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wc = WinchController(wcs)
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winch = WinchControllers.Winch(wcs, set)
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f_low = wcs.f_low
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for i in 1:length(lg)
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# model
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v_wind = V_WIND[i]
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v_act = get_speed(winch)
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force = calc_force(v_wind, v_act)
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set_force(winch, force)
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# controller
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v_set_out = calc_v_set(wc, v_act, force, f_low)
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# update model input
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set_v_set(winch, v_set_out)
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# run integration step
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on_timer(winch)
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on_timer(wc)
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# get values for logging and log them
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status = get_status(wc)
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log(lg; v_wind, v_ro=v_act, acc=get_acc(winch), state=get_state(wc), reset=status[1], active=status[2], force=status[3],
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f_set=status[4], f_err=get_f_err(wc), v_err=get_v_err(wc), v_set=get_v_set(wc), v_set_out, v_set_in=get_v_set_in(wc))
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end
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if return_lg
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return wcs, lg
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end
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# calculate the performance metrics
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-gamma(lg; rms=true)
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end
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function simulate_sc(x::Vector; return_lg::Bool = false)
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wcs = WCSettings(dt=0.02)
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update(wcs)
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wcs.test = true
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wcs.i_speed = x[1] # set the speed controller gain
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wcs.p_speed = x[2] # set the speed controller proportional gain
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wcs.t_blend = x[3] # set the blending time for switching between controllers
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simulate(wcs; return_lg)
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end
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function eval_fct(x)
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bb_outputs = [simulate_sc(x)]
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success = true
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count_eval = true
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return (success, count_eval, bb_outputs)
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end
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function simulate_lfc(x::Vector{Cdouble}; return_lg::Bool = false)
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wcs = WCSettings(dt=0.02)
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update(wcs)
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wcs.test = true
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wcs.pf_low = x[1] # set the lower force controller gain
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wcs.if_low = x[2] # set the lower force controller integral gain
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simulate(wcs; return_lg)
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end
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function simulate_ufc(x::Vector{Cdouble}; return_lg::Bool = false)
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wcs = WCSettings(dt=0.02)
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update(wcs)
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wcs.test = true
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wcs.pf_high = x[1] # set the higher force controller gain
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wcs.if_high = x[2] # set the higher force controller integral gain
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simulate(wcs; return_lg)
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end
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function autotune(controller::WinchControllerState)
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global x, info, lg, TUNED, result
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if TUNED
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load_settings("system_tuned.yaml")
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else
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load_settings("system.yaml")
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end
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wcs = WCSettings(dt=0.02)
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update(wcs)
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wcs.test = true
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if controller == wcsSpeedControl
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println("Autotuning speed controller...")
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# # Define the parameters for the autotuning
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# x0 = [wcs.p_speed, wcs.i_speed, wcs.t_blend] # initial guess for the speed controller gain
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# x, info = bobyqa(simulate_sc, x0;
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# xl = 0.75 .* x0,
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# xu = 1.5 .* x0,
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# rhobeg = maximum([1e-4, minimum(x0)/4]),
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# npt=10,
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# maxfun = 500
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# )
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x0 = [wcs.p_speed, wcs.i_speed, wcs.t_blend] # initial guess for the speed controller gain
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pb = NomadProblem(3, # number of inputs of the blackbox
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1, # number of outputs of the blackbox
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["OBJ"], # type of outputs of the blackbox
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eval_fct;
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lower_bound = 0.75 .* x0,
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upper_bound = 1.5 .* x0)
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result = solve(pb, x0)
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x = result.x_best_feas
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elseif controller == wcsLowerForceLimit
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println("Autotuning lower force limit controller...")
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# Define the parameters for the autotuning
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x0 = [maximum([1e-4, wcs.pf_low]), wcs.if_low] # initial guess for the speed controller gain
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x, info = bobyqa(simulate_lfc, x0;
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xl = 0.25 .* x0,
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xu = 2.0 .* x0,
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rhobeg = maximum([1e-4, minimum(x0)/4]),
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maxfun = 500
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)
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elseif controller == wcsUpperForceLimit
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println("Autotuning upper force control...")
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# Define the parameters for the autotuning
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x0 = [maximum([2e-5, wcs.pf_high]), wcs.if_high] # initial guess for the speed controller gain
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x, info = bobyqa(simulate_lfc, x0;
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xl = 0.25 .* x0,
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xu = 2.0 .* x0,
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rhobeg = maximum([2e-5, minimum(x0)/4]),
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maxfun = 500
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)
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else
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error("Unknown controller state: $controller")
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return
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end
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println("Autotuning results: $x")
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# println("Iterations: $(info.nf)")
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# println(PRIMA.reason(info.status))
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if true
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println("Running simulation with tuned parameters...")
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TUNED = true
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if controller == wcsSpeedControl
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wcs, lg = simulate_sc(x; return_lg=true)
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elseif controller == wcsLowerForceLimit
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wcs, lg = simulate_lfc(x; return_lg=true)
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elseif controller == wcsUpperForceLimit
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wcs, lg = simulate_ufc(x; return_lg=true)
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end
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println("\nPerformance of force controllers: $(round(100*(1-f_err(lg)), digits=2)) %")
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println("Performance of speed controller: $(round(100*(1-v_err(lg)), digits=2)) %")
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println("Damage: $(round(100*(damage(lg)), digits=2)) %")
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println("Damage with rms: $(round(100*(damage(lg; rms=true)), digits=2)) %")
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println("Combined performance γ: $(round(-100*result.bbo_best_feas[1], digits=2)) %")
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return wcs
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else
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println("Autotuning failed: $(PRIMA.reason(info.status))")
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return nothing
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end
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end
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function copy_settings()
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cp("data/wc_settings.yaml", "data/wc_settings_tuned.yaml"; force=true)
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end
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function change_value(lines, varname, value::Union{Integer, Float64})
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KiteUtils.change_value(lines, varname, repr(round(value, digits=4)))
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end
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function update_settings(wcs::WCSettings)
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lines = KiteUtils.readfile("data/wc_settings_tuned.yaml")
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lines = change_value(lines, "i_speed:", wcs.i_speed)
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lines = change_value(lines, "p_speed:", wcs.p_speed)
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lines = change_value(lines, "t_blend:", wcs.t_blend)
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lines = change_value(lines, "pf_low:", wcs.pf_low)
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lines = change_value(lines, "if_low:", wcs.if_low)
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lines = change_value(lines, "pf_high:", wcs.pf_high)
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lines = change_value(lines, "if_high:", wcs.if_high)
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KiteUtils.writefile(lines, "data/wc_settings_tuned.yaml")
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end
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function tune_all()
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wcs = autotune(wcsSpeedControl)
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if ! isnothing(wcs)
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copy_settings()
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update_settings(wcs)
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println()
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wcs = autotune(wcsLowerForceLimit)
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if ! isnothing(wcs)
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update_settings(wcs)
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println()
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wcs = autotune(wcsUpperForceLimit)
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if ! isnothing(wcs)
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update_settings(wcs)
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end
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end
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@info "Tuned settings saved to data/wc_settings_tuned.yaml"
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end
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end
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tune_all()
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tune_all()
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# autotune(wcsUpperForceControl)

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