Parameter Estimation in a Dynamic Systems

K. Schittkowski: Progress in Optimization, X. Yang et al. eds., Kluwer Academic Publishers, 183 - 204 (2000)
Abstract: 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 analysis tools. A list of possible appplications is included.


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