Hello,

I would like to start with `Optim.jl`

to optimize some dynamical systems. The following code should optmize the parameters of a linear output error model which approximates a nonlinear system.

```
using Optim
function system(u_k_1::Array{Float64})
y_k_1 = zeros(size(u_k_1))
for i in 2:length(u_k_1)
y_k_1[i] = 0.2 * ((atan(8.0 * u_k_1[i-1] - 4.0) + atan(4.0)) / (2.0 * atan(4.0))) + 0.8 * y_k_1[i-1]
end
return y_k_1
end
u = [1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 1.0; 0.25; 0.25; 0.25; 0.25; 0.25; 0.25; 0.25; 0.75; 0.75; 0.75; 0.75; 0.75; 0.75; 0.75; 0.5; 0.5; 0.5; 0.5; 0.5; 0.5; 0.5; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0; 0.0]
y = vec(system(u))
order_x=1
order_y=1
x0 = rand(order_x+order_y)
N=length(u)
e = zeros(N)
y_hat = zeros(N)
function f(x)
for i in 2:N
y_hat[i] = x[1]*u[i-1] - x[2] * y_hat[i-1]
e[i] = abs2(y[i]-y_hat[i])
end
return sum(e)
end
optimize(f, x0, LBFGS(); autodiff = :forward)
```

I get the following error message:

ERROR: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{typeof(f), Float64}, Float64, 2})

This is my first attempt to use `Optim.jl`

, so I’m quite unfamiliar with API. Can somebody tell me what I’ve to do to solve my problem?

Best regards