Good system simulation

Author: ufechner7

mwes/mwe_05.jl

@@ -0,0 +1,87 @@
+# Linearize the system consisting of the winch and kite
+# input: set_speed
+# output: speed
+
+using Pkg
+if ! ("ControlPlots" ∈ keys(Pkg.project().dependencies))
+    using TestEnv; TestEnv.activate()
+    using Test
+end
+using WinchControllers, WinchModels, KiteUtils, ControlPlots, ControlSystemsBase, FiniteDiff
+import FiniteDiff: finite_difference_jacobian
+
+if isfile("data/system_tuned.yaml")
+    set = load_settings("system_tuned.yaml")
+else
+    set = load_settings("system.yaml")
+end
+wcs = WCSettings(dt=0.02)
+update(wcs)
+wcs.test = true
+
+winch = Winch(wcs, set)
+
+# find equilibrium speed
+function find_equilibrium_speed(winch, set_speed, force, n=10000)
+    last_v_act = 0.0
+    for v_set in range(0.0, 2*set_speed, n)
+        lim_speed = minimum([v_set, set_speed])
+        set_force(winch, force)
+        set_v_set(winch, lim_speed)
+        v_act = get_speed(winch)
+        on_timer(winch)
+        if v_set > 0 && abs(v_act - last_v_act) < 1e-6
+            return v_act
+        end
+        last_v_act = v_act
+    end
+    set_v_set(winch, set_speed)
+    on_timer(winch)
+    @error "Failed to find equilibrium speed"
+end
+
+function motor_dynamics(x, u)
+    # x: state vector, e.g., [v_act]
+    # u: input vector, e.g., [v_set, force]
+    v_act = x[1]
+    v_set, force = u[1], u[2]
+    acc = calc_acceleration(winch.wm, v_act, force; set_speed = v_set)
+    return [acc]
+end
+
+function calc_force(v_wind, v_ro)
+    (v_wind - v_ro)^2 * 4000.0 / 16.0
+end
+
+function system_dynamics(x, u)
+    # x: state vector, e.g., [v_act]
+    # u: input vector, e.g., [v_set, v_wind]
+    v_act = x[1]
+    v_set, v_wind = u[1], u[2]
+    force = calc_force(v_wind, v_act)
+    acc = calc_acceleration(winch.wm, v_act, force; set_speed = v_set)
+    return [acc]
+end
+
+function linearize(winch, v_set, v_wind)
+    force = calc_force(v_wind, v_set)
+    v_act = find_equilibrium_speed(winch, v_set, force)
+    x0 = [v_act]         # State at operating point
+    u0 = [v_set, v_wind]  # Input at operating point
+    A = finite_difference_jacobian(x -> system_dynamics(x, u0), x0)
+    B = finite_difference_jacobian(u -> system_dynamics(x0, u), u0)
+    C = [1.0]
+    D = [0.0 0.0]
+    siso_sys = ss(A, B[:, 1], C, D[:, 1])
+end
+
+for v_wind in range(1, 9, length=9)
+    v_set = 0.57*v_wind
+    @info "Linearizing for v_wind: $v_wind m/s"
+    sys_new = linearize(winch, v_set, v_wind)
+    # @info "System: $sys_new"
+    # @info "Eigenvalues: $(eigvals(sys_new))"
+    bode_plot(sys_new; from=0.76, to=2.85, title="Linearized System, v_wind=1..9 m/s")
+end
+
+# bode_plot(sys_new; to=2, title="Linearized Winch, F=$force N")