Merge pull request #38 from control-toolbox/15-flow-with-variables-no…

…nfixed-ocp

fix t0, tf variable

src/CTFlows.jl

@@ -8,7 +8,7 @@ module CTFlows
     import Base: *
 
     # to be placed in CTBase
-    include("exceptions.jl")
+    include("ctbase.jl")
 
     # --------------------------------------------------------------------------------------------------
     # Aliases for types

src/exceptions.jl → src/ctbase.jl

@@ -1,3 +1,8 @@
+
+#
+variable_dimension(ocp::OptimalControlModel) = ocp.variable_dimension
+
+
 #
 """
 $(TYPEDEF)

src/default.jl

@@ -1,6 +1,22 @@
 # --------------------------------------------------------------------------------------------
 # Default options for flows
 # --------------------------------------------------------------------------------------------
+function __variable(t0, x0, p0, tf, ocp)
+    # if tf is free and ocp has only one variable, then return tf
+    CTBase.has_free_final_time(ocp) && variable_dimension(ocp)==1 && return tf
+
+    # if t0 is free and ocp has only one variable, then return t0
+    CTBase.has_free_initial_time(ocp) && variable_dimension(ocp)==1 && return t0
+
+    # if t0 and tf are free and ocp has only two variables, then return [t0, tf]
+    CTBase.has_free_final_time(ocp) && CTBase.has_free_initial_time(ocp) && variable_dimension(ocp)==2 && return [t0, tf]
+
+    # otherwise return an empty vector of right type to avoid warning performance message from OrdinaryDiffEq
+    z0 = [x0; p0]
+    T  = eltype(z0)
+    return Vector{T}()
+end
+
 function __variable(x0, p0) 
     z0 = [x0; p0]
     T  = eltype(z0)

src/types.jl

@@ -120,12 +120,21 @@ struct OptimalControlFlow <: AbstractFlow{DCoTangent, CoTangent}
 end
 
 # call F.f
-(F::OptimalControlFlow)(args...; kwargs...) = begin
-    F.f(args...; jumps=F.jumps, _t_stops_interne=F.tstops, DiffEqRHS=F.rhs!, kwargs...)
+function (F::OptimalControlFlow)(
+    t0::Time, 
+    x0::State, 
+    p0::Costate, 
+    tf::Time, 
+    v::Variable=__variable(t0, x0, p0, tf, F.ocp); kwargs...)
+    F.f(t0, x0, p0, tf, v; jumps=F.jumps, _t_stops_interne=F.tstops, DiffEqRHS=F.rhs!, kwargs...)
 end
 
 # call F.f and then, construct an optimal control solution
-function (F::OptimalControlFlow)(tspan::Tuple{Time,Time}, x0::State, p0::Costate, v::Variable=__variable(x0, p0); kwargs...) 
+function (F::OptimalControlFlow)(
+    tspan::Tuple{Time,Time}, 
+    x0::State, 
+    p0::Costate, 
+    v::Variable=__variable(tspan[1], x0, p0, tspan[2], F.ocp); kwargs...) 
     ode_sol  = F.f(tspan, x0, p0, v; jumps=F.jumps, _t_stops_interne=F.tstops, DiffEqRHS=F.rhs!, kwargs...)
     flow_sol = OptimalControlFlowSolution(ode_sol, F.feedback_control, F.ocp, v)
     return CTFlows.OptimalControlSolution(flow_sol)

test/test_optimal_control_problem.jl

@@ -144,4 +144,107 @@ function test_optimal_control_problem()
 
     end
 
+    @testset "tf variable" begin
+
+        t0 = 0
+        x0 = 0
+        xf = 1
+
+        @def ocp begin
+            tf ∈ R, variable
+            t ∈ [t0, tf], time
+            x ∈ R, state
+            u ∈ R, control
+            ẋ(t) == tf * u(t)
+            x(t0) == x0
+            x(tf) == xf
+            tf + 0.5∫(u(t)^2) → min
+        end
+
+        u = (x, p, tf) -> tf*p
+        F = Flow(ocp, u)
+
+        # solution
+        tf = (3/2)^(1/4)
+        p0 = 2tf/3
+
+        # tf is provided twice
+        xf_, pf_ = F(t0, x0, p0, tf, tf)
+        Test.@test xf ≈ xf_ atol=1e-6
+
+        # tf is provided once
+        xf_, pf_ = F(t0, x0, p0, tf)
+        Test.@test xf ≈ xf_ atol=1e-6
+
+    end
+
+    @testset "t0 variable" begin
+
+        t0 = 0
+        x0 = 0
+        xf = 1
+
+        @def ocp begin
+            tf ∈ R, variable
+            s ∈ [tf, t0], time
+            x ∈ R, state
+            u ∈ R, control
+            ẋ(s) == - tf * u(s)
+            x(tf) == xf
+            x(t0) == x0
+            tf - 0.5∫(u(s)^2) → min
+        end
+
+        u = (x, p, tf) -> tf*p
+        F = Flow(ocp, u)
+
+        # solution
+        tf = (3/2)^(1/4)
+        p0 = -2tf/3
+
+        # tf is provided twice: it plays the role of the initial time
+        x0_, pf_ = F(tf, xf, p0, t0, tf)
+        Test.@test x0 ≈ x0_ atol=1e-6
+
+        # tf is provided once
+        x0_, pf_ = F(tf, xf, p0, t0)
+        Test.@test x0 ≈ x0_ atol=1e-6
+
+    end
+
+
+    @testset "t0 and tf variable" begin
+
+        x0 = 0
+        xf = 1
+
+        @def ocp begin
+            v = (t0, tf) ∈ R^2, variable
+            t ∈ [t0, tf], time
+            x ∈ R, state
+            u ∈ R, control
+            ẋ(t) == tf * u(t) + t0
+            x(t0) == x0
+            x(tf) == xf
+            (t0^2 + tf) + 0.5∫(u(t)^2) → min
+        end
+
+        u = (x, p, v) -> v[2]*p
+        F = Flow(ocp, u)
+
+        # solution
+        t0 = 0
+        tf = (3/2)^(1/4)
+        p0 = 2tf/3
+
+        # t0, tf are provided twice
+        xf_, pf_ = F(t0, x0, p0, tf, [t0, tf])
+        Test.@test xf ≈ xf_ atol=1e-6
+
+        # t0, tf are provided once
+        xf_, pf_ = F(t0, x0, p0, tf)
+        Test.@test xf ≈ xf_ atol=1e-6
+
+    end
+
 end