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debug: revert allocation-free linearize! to avoid NonLinModel type-instability #160

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Feb 16, 2025
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debug: revert allocation-free linearize! to avoid NonLinModel type-instability #160

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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "ModelPredictiveControl"
uuid = "61f9bdb8-6ae4-484a-811f-bbf86720c31c"
authors = ["Francis Gagnon"]
version = "1.3.2"
version = "1.3.3"

[deps]
ControlSystemsBase = "aaaaaaaa-a6ca-5380-bf3e-84a91bcd477e"
Expand Down
55 changes: 17 additions & 38 deletions src/model/linearization.jl
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Original file line number Diff line number Diff line change
@@ -1,31 +1,3 @@

function jacobianA!(A, jb::JacobianBuffer, model::SimModel, x, u, d)
jb.x .= x; jb.u .= u; jb.d .= d
return ForwardDiff.jacobian!(A, jb.f_x!, jb.xnext, jb.x, jb.f_x_cfg)
end
jacobianA!( _ , _ , model::LinModel, _ , _ , _ ) = model.A
function jacobianBu!(Bu, jb::JacobianBuffer, model::SimModel, x, u, d)
jb.x .= x; jb.u .= u; jb.d .= d
return ForwardDiff.jacobian!(Bu, jb.f_u!, jb.xnext, jb.u, jb.f_u_cfg)
end
jacobianBu!( _ , _ , model::LinModel, _ , _ , _ ) = model.Bu
function jacobianBd!(Bd, jb::JacobianBuffer, model::SimModel, x, u, d)
jb.x .= x; jb.u .= u; jb.d .= d
return ForwardDiff.jacobian!(Bd, jb.f_d!, jb.xnext, jb.d, jb.f_d_cfg)
end
jacobianBd!( _ , _ , model::LinModel, _ , _ , _ ) = model.Bd
function jacobianC!(C, jb::JacobianBuffer, model::SimModel, x, d)
jb.x .= x; jb.d .= d
return ForwardDiff.jacobian!(C, jb.h_x!, jb.y, jb.x, jb.h_x_cfg)
end
jacobianC!( _ , _ , model::LinModel, _ , _ ) = model.C
function jacobianDd!(Dd, jb::JacobianBuffer, model::SimModel, x, d)
jb.x .= x; jb.d .= d
return ForwardDiff.jacobian!(Dd, jb.h_d!, jb.y, jb.d, jb.h_d_cfg)
end
jacobianDd!( _ , _ , model::LinModel, _ , _ ) = model.Dd


"""
LinModel(model::NonLinModel; x=model.x0+model.xop, u=model.uop, d=model.dop)

Expand Down Expand Up @@ -120,8 +92,8 @@ end

Linearize `model` and store the result in `linmodel` (in-place).

The keyword arguments are identical to [`linearize`](@ref). The code is allocation-free if
`model` simulations does not allocate.
The keyword arguments are identical to [`linearize`](@ref). The code allocates a small
amount of memory to compute the Jacobians.

# Examples
```jldoctest
Expand All @@ -137,8 +109,8 @@ julia> linearize!(linmodel, model, x=[20.0], u=[0.0]); linmodel.A
```
"""
function linearize!(
linmodel::LinModel, model::SimModel; x=model.x0+model.xop, u=model.uop, d=model.dop
)
linmodel::LinModel{NT}, model::SimModel; x=model.x0+model.xop, u=model.uop, d=model.dop
) where NT<:Real
nonlinmodel = model
buffer = nonlinmodel.buffer
# --- remove the operating points of the nonlinear model (typically zeros) ---
Expand All @@ -147,12 +119,19 @@ function linearize!(
d0 .= d .- nonlinmodel.dop
x0 .= x .- nonlinmodel.xop
# --- compute the Jacobians at linearization points ---
jb = nonlinmodel.buffer.jacobian
jacobianA!(linmodel.A, jb, nonlinmodel, x0, u0, d0)
jacobianBu!(linmodel.Bu, jb, nonlinmodel, x0, u0, d0)
jacobianBd!(linmodel.Bd, jb, nonlinmodel, x0, u0, d0)
jacobianC!(linmodel.C, jb, nonlinmodel, x0, d0)
jacobianDd!(linmodel.Dd, jb, nonlinmodel, x0, d0)
A::Matrix{NT}, Bu::Matrix{NT}, Bd::Matrix{NT} = linmodel.A, linmodel.Bu, linmodel.Bd
C::Matrix{NT}, Dd::Matrix{NT} = linmodel.C, linmodel.Dd
xnext0::Vector{NT}, y0::Vector{NT} = linmodel.buffer.x, linmodel.buffer.y
myf_x0!(xnext0, x0) = f!(xnext0, nonlinmodel, x0, u0, d0, model.p)
myf_u0!(xnext0, u0) = f!(xnext0, nonlinmodel, x0, u0, d0, model.p)
myf_d0!(xnext0, d0) = f!(xnext0, nonlinmodel, x0, u0, d0, model.p)
myh_x0!(y0, x0) = h!(y0, nonlinmodel, x0, d0, model.p)
myh_d0!(y0, d0) = h!(y0, nonlinmodel, x0, d0, model.p)
ForwardDiff.jacobian!(A, myf_x0!, xnext0, x0)
ForwardDiff.jacobian!(Bu, myf_u0!, xnext0, u0)
ForwardDiff.jacobian!(Bd, myf_d0!, xnext0, d0)
ForwardDiff.jacobian!(C, myh_x0!, y0, x0)
ForwardDiff.jacobian!(Dd, myh_d0!, y0, d0)
# --- compute the nonlinear model output at operating points ---
xnext0, y0 = linmodel.buffer.x, linmodel.buffer.y
h!(y0, nonlinmodel, x0, d0, model.p)
Expand Down
15 changes: 7 additions & 8 deletions src/model/nonlinmodel.jl
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
struct NonLinModel{
NT<:Real, F<:Function, H<:Function, P<:Any, DS<:DiffSolver, SMB<:SimModelBuffer
NT<:Real, F<:Function, H<:Function, P<:Any, DS<:DiffSolver
} <: SimModel{NT}
x0::Vector{NT}
f!::F
Expand All @@ -21,10 +21,10 @@ struct NonLinModel{
yname::Vector{String}
dname::Vector{String}
xname::Vector{String}
buffer::SMB
buffer::SimModelBuffer{NT}
function NonLinModel{NT}(
f!::F, h!::H, Ts, nu, nx, ny, nd, p::P, solver::DS, buffer::SMB
) where {NT<:Real, F<:Function, H<:Function, P<:Any, DS<:DiffSolver, SMB<:SimModelBuffer}
f!::F, h!::H, Ts, nu, nx, ny, nd, p::P, solver::DS
) where {NT<:Real, F<:Function, H<:Function, P<:Any, DS<:DiffSolver}
Ts > 0 || error("Sampling time Ts must be positive")
uop = zeros(NT, nu)
yop = zeros(NT, ny)
Expand All @@ -37,7 +37,8 @@ struct NonLinModel{
xname = ["\$x_{$i}\$" for i in 1:nx]
x0 = zeros(NT, nx)
t = zeros(NT, 1)
return new{NT, F, H, P, DS, SMB}(
buffer = SimModelBuffer{NT}(nu, nx, ny, nd)
return new{NT, F, H, P, DS}(
x0,
f!, h!,
p,
Expand Down Expand Up @@ -144,9 +145,7 @@ function NonLinModel{NT}(
isnothing(solver) && (solver=EmptySolver())
f!, h! = get_mutating_functions(NT, f, h)
f!, h! = get_solver_functions(NT, solver, f!, h!, Ts, nu, nx, ny, nd)
jacobian = JacobianBuffer{NT}(f!, h!, nu, nx, ny, nd, p)
buffer = SimModelBuffer{NT}(nu, nx, ny, nd, jacobian)
return NonLinModel{NT}(f!, h!, Ts, nu, nx, ny, nd, p, solver, buffer)
return NonLinModel{NT}(f!, h!, Ts, nu, nx, ny, nd, p, solver)
end

function NonLinModel(
Expand Down
21 changes: 10 additions & 11 deletions src/sim_model.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -34,9 +34,9 @@ struct JacobianBuffer{
CHX<:ForwardDiff.JacobianConfig
}
xnext::Vector{NT}
u::Vector{NT}
x::Vector{NT}
y::Vector{NT}
u::Vector{NT}
d::Vector{NT}
f_x!::FX
f_u!::FU
Expand All @@ -48,34 +48,33 @@ struct JacobianBuffer{
f_d_cfg::CFD
h_x_cfg::CHX
h_d_cfg::CHU

end

"""
JacobianBuffer(NT::DataType, f!::Function, h!::Function, nu, nx, ny, nd)
JacobianBuffer(NT::DataType, f!::Function, h!::Function, nx, nu, ny, nd)

Buffer object for calling `ForwardDiff.jacobian!` on `SimModel` without any allocation.
"""
function JacobianBuffer{NT}(
f!::Function, h!::Function, nu::Int, nx::Int, ny::Int, nd::Int, p
f!::Function, h!::Function, nx::Int, nu::Int, ny::Int, nd::Int
) where NT <: Real
xnext = Vector{NT}(undef, nx)
u = Vector{NT}(undef, nu)
x = Vector{NT}(undef, nx)
y = Vector{NT}(undef, ny)
u = Vector{NT}(undef, nu)
d = Vector{NT}(undef, nd)
f_x!(xnext, x) = f!(xnext, x, u, d, p)
f_u!(xnext, u) = f!(xnext, x, u, d, p)
f_d!(xnext, d) = f!(xnext, x, u, d, p)
h_x!(y, x) = h!(y, x, d, p)
h_d!(y, d) = h!(y, x, d, p)
f_x!(y, x) = f!(y, x, u, d)
f_u!(y, u) = f!(y, x, u, d)
f_d!(y, d) = f!(y, x, u, d)
h_x!(y, x) = h!(y, x, d)
h_d!(y, d) = h!(y, x, d)
f_x_cfg = ForwardDiff.JacobianConfig(f_x!, xnext, x)
f_u_cfg = ForwardDiff.JacobianConfig(f_u!, xnext, u)
f_d_cfg = ForwardDiff.JacobianConfig(f_d!, xnext, d)
h_x_cfg = ForwardDiff.JacobianConfig(h_x!, y, x)
h_d_cfg = ForwardDiff.JacobianConfig(h_d!, y, d)
return JacobianBuffer(
xnext, u, x, y, d,
xnext, x, y, u, d,
f_x!, f_u!, f_d!, h_x!, h_d!,
f_x_cfg, f_u_cfg, f_d_cfg, h_x_cfg, h_d_cfg
)
Expand Down