v0.8.0

Author: ocots

Project.toml

@@ -1,7 +1,7 @@
 name = "OptimalControl"
 uuid = "5f98b655-cc9a-415a-b60e-744165666948"
 authors = ["Olivier Cots <[email protected]>"]
-version = "0.7.8"
+version = "0.8.0"
 
 [deps]
 CTBase = "54762871-cc72-4466-b8e8-f6c8b58076cd"
@@ -11,8 +11,8 @@ CTProblems = "45d9ea3f-a92f-411f-833f-222dd4fb9cd8"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 
 [compat]
-CTBase = "0.8"
-CTDirect = "0.5"
+CTBase = "0.9"
+CTDirect = "0.6"
 CTFlows = "0.3"
 CTProblems = "0.5"
 julia = "1.8"

test/Project.toml

@@ -1,7 +1,8 @@
 [deps]
 CTProblems = "45d9ea3f-a92f-411f-833f-222dd4fb9cd8"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-MINPACK = "4854310b-de5a-5eb6-a2a5-c1dee2bd17f9"
+NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]

test/runtests.jl

@@ -1,8 +1,9 @@
 using OptimalControl
 using Test
 using LinearAlgebra
-using MINPACK
 using CTProblems
+using SciMLBase
+using NonlinearSolve
 
 #
 @testset verbose = true showtiming = true "Optimal control tests" begin

test/test_basic.jl

@@ -10,7 +10,7 @@ function test_basic()
         ∫( 0.5u(t)^2 ) → min
     end
 
-    sol = solve(ocp)
+    sol = OptimalControl.solve(ocp)
     @test sol.objective ≈ 6 atol=1e-2
 
 end

test/test_goddard_direct.jl

@@ -8,7 +8,7 @@ ocp = prob.model
 init = (state=[1.01, 0.05, 0.8], control=0.1, variable=0.2)
 
 # solve
-sol = solve(ocp, grid_size=10, print_level=5, init=init)
+sol = OptimalControl.solve(ocp, grid_size=10, print_level=5, init=init)
 
 # test
 @test sol.objective ≈ prob.solution.objective atol=5e-3

test/test_goddard_indirect.jl

@@ -95,18 +95,21 @@ s_guess_sol = [-0.02456074767656735,
 ξ0 = [ p0 ; t1 ; t2 ; t3 ; tf ]
 
 #
-foo!(s, ξ) = shoot!(s, ξ[1:3], ξ[4], ξ[5], ξ[6], ξ[7])
-sol = fsolve(foo!, ξ0, show_trace=true); println(sol)
+foo!(s, ξ, λ) = shoot!(s, ξ[1:3], ξ[4], ξ[5], ξ[6], ξ[7])
+#sol = fsolve(foo!, ξ0, show_trace=true); println(sol)
+prob = NonlinearProblem(foo!, ξ0)
+sol = NonlinearSolve.solve(prob)
 
-p0 = sol.x[1:3]
-t1 = sol.x[4]
-t2 = sol.x[5]
-t3 = sol.x[6]
-tf = sol.x[7];
+p0 = sol.u[1:3]
+t1 = sol.u[4]
+t2 = sol.u[5]
+t3 = sol.u[6]
+tf = sol.u[7];
 
 shoot!(s, p0, t1, t2, t3, tf)
 
-@test sol.converged
+#@test sol.converged
+@test SciMLBase.successful_retcode(sol)
 @test norm(s) < 1e-6
 
 end

test/test_init.jl

@@ -10,22 +10,22 @@ function test_init()
 
     # initial guess (constant state and control)
     init = (state=[-0.5, 0.2], control=0.5)
-    sol = solve(ocp, grid_size=N, init=init)
+    sol = OptimalControl.solve(ocp, grid_size=N, init=init)
     @test sol.objective ≈ prob.solution.objective atol=tol
 
     # initial guess (constant state and functional control)
     init = (state=[-0.5, 0.2], control=t->6-12*t)
-    sol = solve(ocp, grid_size=N, init=init)
+    sol = OptimalControl.solve(ocp, grid_size=N, init=init)
     @test sol.objective ≈ prob.solution.objective atol=tol
 
     # initial guess (functional state and constant control)
     init = (state=t->[-1+t, t*(t-1)], control=0.5)
-    sol = solve(ocp, grid_size=N, init=init)
+    sol = OptimalControl.solve(ocp, grid_size=N, init=init)
     @test sol.objective ≈ prob.solution.objective atol=tol
 
     # initial guess (functional state and functional control)
     init = (state=t->[-1+t, t*(t-1)], control=t->6-12*t)
-    sol = solve(ocp, grid_size=N, init=init)
+    sol = OptimalControl.solve(ocp, grid_size=N, init=init)
     @test sol.objective ≈ prob.solution.objective atol=tol
 
 end