Minimum Working Example (MWE) of a SINDy problem showing error

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Hello all,
The following is a MWE for a problem I am working on. Here I am trying to fit Qgen as a function of I,u[1],u[2] using a SINDy algorithm but I am running into errors. Here is the code

using  OrdinaryDiffEq
using Plots
using DataDrivenSparse, DataDrivenDiffEq
using StableRNGs
using LinearAlgebra

rng = StableRNG(1111)

# Generating synthetic data 

function actualODE!(du,u,p,t,T∞,I)
    
    Cbat  =  5*3600 
    du[1] = -I/Cbat

    C₁ = -0.00153 # Unit is s-1
    C₂ = 0.020306 # Unit is K/J

    R0 = 0.03 # Resistance set a 30mohm

    Qgen =(I^2)*R0 # This is just an approximate value. In actual case Qgen = f(I,u[1],u[2])

    du[2] = (C₁*(u[2]-T∞)) + (C₂*Qgen)

end

t1 = collect(0:1:3400)
T∞1,I1 = 298.15,5

t2 = collect(0:1:6000)
T∞2,I2 = 273.15,2.5

actualODE1!(du,u,p,t) = actualODE!(du,u,p,t,T∞1,I1)
actualODE2!(du,u,p,t) = actualODE!(du,u,p,t,T∞2,I2)

prob1 = ODEProblem(actualODE1!,[1.0,T∞1],(t1[1],t1[end]))
prob2 = ODEProblem(actualODE2!,[1.0,T∞2],(t2[1],t2[end]))

sol1 = Array(solve(prob1,Tsit5(),saveat=t1))
sol2 = Array(solve(prob2,Tsit5(),saveat=t2))

# Plotting the results

P = plot(layout = (2,2),size = (600,400))

plot!(P[1],t1,sol1[2,:],label="Ambient Temp 25C",xlabel="Time (s)",ylabel="Temperature (K)")
plot!(P[2],t1,sol1[1,:],label="SOC",xlabel="Time (s)",ylabel="SOC")

plot!(P[3],t2,sol2[2,:],label="Ambient Temp 0C",xlabel="Time (s)",ylabel="Temperature (K)")
plot!(P[4],t2,sol2[1,:],label="SOC",xlabel="Time (s)",ylabel="SOC") 
display(P)

# The current vector
I1_t = fill(I1,length(t1))
I2_t = fill(I2,length(t2))

# The heat generation rate vector
Qgen1 = (I1_t.^2).*0.03
Qgen2 = (I2_t.^2).*0.03

# Trying to perform SINDy so that we obtain a representation of Qgen as a function of I,u[1],u[2]

# Creating input vector
xin1 = zeros(3,length(t1))
for i in eachindex(t1)
    It1 = I1_t[i]
    xin1[:,i] = [It1,sol1[1,i],sol1[2,i]]
end

xin2 = zeros(3,length(t2))
for i in eachindex(t2)
    It2 = I2_t[i]
    xin2[:,i] = [It2,sol2[1,i],sol2[2,i]]
end

G1 = reshape(Qgen1,1,length(t1))
G2 = reshape(Qgen2,1,length(t2))


X̂ = hcat(xin1,xin2)
Ŷ = hcat(G1,G2)

N = size(X̂,1)
@variables u[1:N]
b = polynomial_basis(u,2)
basis = Basis(b,u)
nn_problem = DirectDataDrivenProblem(X̂,Ŷ)

λ = 1e-1
opt = ADMM(λ)
options = DataDrivenCommonOptions()
nn_res = solve(nn_problem,basis,opt,options=options)

The following error is shown

ERROR: MethodError: no method matching zero(::Type{Any})
This error has been manually thrown, explicitly, so the method may exist but be intentionally marked as unimplemented.

Closest candidates are:
  zero(::Type{Union{Missing, T}}) where T
   @ Base missing.jl:105
  zero(::Type{Union{}}, Any...)
   @ Base number.jl:315
  zero(::Type{Symbolics.TermCombination})
   @ Symbolics C:\Users\Kalath_A\.julia\packages\Symbolics\xD5Pj\src\linearity.jl:51    
  ...

Stacktrace:
  [1] zero(::Type{Any})
    @ Base .\missing.jl:106
  [2] reduce_empty(::typeof(+), ::Type{Any})
    @ Base .\reduce.jl:335
  [3] reduce_empty(::typeof(Base.add_sum), ::Type{Any})
    @ Base .\reduce.jl:342
  [4] mapreduce_empty(::typeof(abs2), op::Function, T::Type)
    @ Base .\reduce.jl:363
  [5] reduce_empty(op::Base.MappingRF{typeof(abs2), typeof(Base.add_sum)}, ::Type{Any}) 
    @ Base .\reduce.jl:350
  [6] reduce_empty_iter
    @ .\reduce.jl:373 [inlined]
  [7] mapreduce_empty_iter(f::Function, op::Function, itr::Matrix{Any}, ItrEltype::Base.HasEltype)
    @ Base .\reduce.jl:369
  [8] _mapreduce(f::typeof(abs2), op::typeof(Base.add_sum), ::IndexLinear, A::Matrix{Any})
    @ Base .\reduce.jl:421
  [9] _mapreduce_dim(f::Function, op::Function, ::Base._InitialValue, A::Matrix{Any}, ::Colon)
    @ Base .\reducedim.jl:334
 [10] mapreduce
    @ .\reducedim.jl:326 [inlined]
 [11] _sum
    @ .\reducedim.jl:984 [inlined]
 [12] sum(f::Function, a::Matrix{Any})
    @ Base .\reducedim.jl:980
 [13] DataDrivenSolution(b::Basis{…}, p::DataDrivenProblem{…}, alg::ADMM{…}, result::Vector{…}, internal_problem::DataDrivenDiffEq.InternalDataDrivenProblem{…}, retcode::DDReturnCode)
    @ DataDrivenDiffEq C:\Users\Kalath_A\.julia\packages\DataDrivenDiffEq\bgE8Q\src\solution.jl:38
 [14] solve!(ps::DataDrivenDiffEq.InternalDataDrivenProblem{…})
    @ DataDrivenSparse C:\Users\Kalath_A\.julia\packages\DataDrivenSparse\5sJbZ\src\commonsolve.jl:21
 [15] solve(::DataDrivenProblem{…}, ::Vararg{…}; kwargs::@Kwargs{…})
    @ CommonSolve C:\Users\Kalath_A\.julia\packages\CommonSolve\JfpfI\src\CommonSolve.jl:23
 [16] top-level scope
    @ c:\Users\Kalath_A\OneDrive - University of Warwick\PhD\ML Notebooks\Neural ODE\Julia\T Mixed\With Qgen multiplied with I\squareQgen\2_20_20_tanh\PEM-UDE\MWE_UDE_PEM.jl:92
Some type information was truncated. Use `show(err)` to see complete types.

In the real problem , I have a trained neural network Qgen(I,u[1],u[2]) which I am trying to fit using SINDy algorithms but similar error is shown.

Can anybody help me? I am new to this field and any help would be much appreciated.