Parameter Estimation in a Dynamic Systems
K. Schittkowski: Progress in Optimization, X. Yang et al. eds., Kluwer Academic Publishers, 183 - 204 (2000)
The intention of the paper is to present a review on numerical methods
to identify parameters in systems
of ordinary differential equations, differential algebraic equations, or
systems of one-dimensional time-dependent partial differential equations
with or without algebraic equations.
Proceeding from given experimental data, i.e. observation times and
measurements, the minimum least squares distance of measured data from a
fitting criterion is computed, that depends on the solution
of the dynamic system.
We present a typical black box approach that is easily
implemented proceeding from some standard numerical
A list of possible appplications is included.