Add control function and improve serialization

Project.toml

@@ -86,7 +86,7 @@ StatsBase = "0.34"
 SteadyStateDiffEq = "2.5"
 Suppressor = "0.2.8"
 SymbolicIndexingInterface = "0.3"
-SymbolicUtils = "3.25"
+SymbolicUtils = "~3.29"
 TOML = "1.0.3"
 Tar = "1.10.0"
 Test = "1"

README.md

@@ -1,6 +1,6 @@
 <!--
 SPDX-FileCopyrightText: 2025 Uwe Fechner, Bart van de Lint
-SPDX-License-Identifier: MIT
+SPDX-License-Identifier: MPL-2.0
 -->
 
 # SymbolicAWEModels

docs/src/private_functions.md

@@ -65,7 +65,11 @@ SymbolicAWEModels.linear_vsm_eqs!
 SymbolicAWEModels.force_eqs!
 SymbolicAWEModels.linearize_vsm!
 SymbolicAWEModels.jacobian
-SymbolicAWEModels.generate_getters
+SymbolicAWEModels.load_serialized_model!
+SymbolicAWEModels.generate_getters!
+SymbolicAWEModels.maybe_create_lin_prob!
+SymbolicAWEModels.maybe_create_control_functions!
+SymbolicAWEModels.maybe_create_prob!
 ```
 
 ## Utility and Internal Functions

examples/ram_air_kite.jl

@@ -25,13 +25,8 @@ steering_magnitude = 10.0      # Magnitude of steering input [Nm]
 
 # Initialize model
 set = Settings("system.yaml")
-
-@info "Creating SymbolicAWEModel:"
 sam = SymbolicAWEModel(set)
-toc()
 SymbolicAWEModels.init!(sam)
-@info "System initialized at:"
-toc()
 
 find_steady_state!(sam)
 bias = 0.15
@@ -40,8 +35,4 @@ if set.physical_model == "4_attach_ram"
 end
 sl, _ = sim_oscillate!(sam; dt, total_time, vsm_interval, steering_freq, steering_magnitude, 
                          bias, prn=true)
-@info "Simulated at:"
-toc()
-display(plot(sam.sys_struct, sl))
-@info "Plotted at:"
-toc()
+nothing

examples/simple_tuned_model.jl

@@ -20,7 +20,7 @@ init!(tether_sam)
 
 simple_set = Settings("system.yaml")
 simple_sam = SymbolicAWEModel(simple_set, "simple_ram")
-init!(simple_sam)
+init!(simple_sam; create_control_func=true)
 
 sim_oscillate!(sam; total_time=1.0)
 SymbolicAWEModels.copy_to_simple!(sam, tether_sam, simple_sam)

src/SymbolicAWEModels.jl

@@ -28,6 +28,7 @@ using ControlSystemsBase
 using RecipesBase
 using StaticArrays
 using SymbolicIndexingInterface
+using SymbolicIndexingInterface: AbstractIndexer
 
 # --- Solvers (Nonlinear, Differential Equations) ---
 using NonlinearSolve

src/generate_system.jl

@@ -270,7 +270,6 @@ function force_eqs!(s, system, psys, pset, eqs, defaults, guesses;
                 F .+= 0.5drag_force[:, segment.idx]
             end
         end
-        @assert !iszero(mass)
 
         eqs = [
             eqs
@@ -362,7 +361,7 @@ function force_eqs!(s, system, psys, pset, eqs, defaults, guesses;
                                                 acc[:, point.idx] ⋅ axis * axis,
                                                 acc[:, point.idx]
                                         )
-                acc[:, point.idx]    ~ point_force[:, point.idx] / mass - bridle_damp_vec
+                acc[:, point.idx]    ~ point_force[:, point.idx] ./ mass - bridle_damp_vec
             ]
             defaults = [
                 defaults

src/linearize.jl

@@ -45,10 +45,10 @@ velocity, twist angles), linearizes the VSM aerodynamics around this operating p
 and updates the Jacobian (`vsm_jac`) and the steady-state forces (`vsm_x`) in the
 `SystemStructure`. This is typically called periodically during a simulation.
 """
-function linearize_vsm!(s::SymbolicAWEModel, integ=s.integrator)
-    wings = s.sys_struct.wings
+function linearize_vsm!(sam::SymbolicAWEModel, integ=sam.integrator)
+    wings = sam.sys_struct.wings
     if length(wings) > 0
-        vsm_y = s.get_vsm_y(integ)
+        vsm_y = sam.get_vsm_y(integ)
         for wing in wings
             wing.vsm_y .= vsm_y[wing.idx,:]
             res = VortexStepMethod.linearize(
@@ -57,13 +57,13 @@ function linearize_vsm!(s::SymbolicAWEModel, integ=s.integrator)
                 wing.vsm_y;
                 va_idxs=1:3, 
                 omega_idxs=4:6,
-                theta_idxs=7:6+length(s.sys_struct.groups),
-                moment_frac=s.sys_struct.groups[1].moment_frac
+                theta_idxs=7:6+length(sam.sys_struct.groups),
+                moment_frac=sam.sys_struct.groups[1].moment_frac
             )
             wing.vsm_jac .= res[1]
             wing.vsm_x .= res[2]
         end
-        s.set_psys(integ, s.sys_struct)
+        sam.set_sys(integ, sam.sys_struct)
     end
     nothing
 end
@@ -85,13 +85,13 @@ calculate the A, B, C, and D matrices for the complete, high-order system.
 # Returns
 - `LinType`: A NamedTuple `(A, B, C, D)` containing the state-space matrices.
 """
-function linearize!(s::SymbolicAWEModel; set_values=s.get_set_values(s.integrator))
-    isnothing(s.lin_prob) && error("Run init! with remake=true and lin_outputs=...")
-    s.set_lin_set_values(s.lin_prob, set_values)
-    s.set_psys(s.lin_prob, s.sys_struct)
-    s.set_set(s.lin_prob, s.set)
-    s.lin_model = solve(s.lin_prob)[1]
-    return s.lin_model
+function linearize!(sam::SymbolicAWEModel; set_values=sam.get_set_values(sam.integrator))
+    isnothing(sam.lin_prob) && error("Run init! with remake=true and lin_outputs=...")
+    sam.set_lin_set_values(sam.lin_prob, set_values)
+    sam.set_lin_sys(sam.lin_prob, sam.sys_struct)
+    sam.set_lin_set(sam.lin_prob, sam.set)
+    sam.lin_model = solve(sam.lin_prob)[1]
+    return sam.lin_model
 end
 
 """

src/precompile.jl

@@ -1,5 +1,5 @@
-# Copyright (c) 2024 Uwe Fechner, Bart van de Lint
-# SPDX-License-Identifier: MIT
+# Copyright (c) 2025 Uwe Fechner, Bart van de Lint
+# SPDX-License-Identifier: MPL-2.0
 
 """
     create_model_archive(source_dir, archive_path)

src/simulate.jl

@@ -162,7 +162,9 @@ function sim_oscillate!(
     set_values = zeros(Float64, steps, num_winches)
 
     if prn
-        @info "Generating oscillating steering commands..."
+        @info "Simulating using oscillating steering inputs\n" *
+              "\twith frequency = $steering_freq Hz\n" *
+              "\tand magnitude = $steering_magnitude N."
     end
 
     for step in 1:steps