The problem in parameter identification
is to estimate unknown parameters 
of the dynamic model.
(inverse problem).
Measurement values 
of an experiment are given
which have been obtained at the l times
where 
.
Measurement values at times are quantities depending on
,
or
.
The efficiency of the numerical computations can be improved if the case of directly measured state variables is treated separately from the case that only functions of them have been measured.
Positive real constants 
can be used in order to weight
the deviations from the -values
in the nonlinear least squares objective
The parameters have to minimize 
subject
to the differential-algebraic equations (1),
the boundary conditions (2),
and the inequality constraints (3).
The resulting nonlinear least squares problem with nonlinear constraints can be solved by either a generalized Gauss-Newton or a Sequential Quadratic Programming Method.
