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Parameter Estimation

Mathematical modeling of dynamic processes in science and engineering frequently leads to large systems of differential-algebraic equations (DAE) or partial differential-algebraic equations (PDAE), which are used in process simulation. Typically, these mathematical models involve unknown model parameters that have to be fitted against experimental data to ensure a good match between mathematical model and reality.

For the solution of such problems, boundary value problem (BVP) methods with multiple shooting or collocation discretization have proven to be very successful.

The basic idea is to treat the discretized DAE model as a nonlinear constraint of the optimization problem. This problem is then solved by algorithms that allow infeasible points, such as generalized Gauss-Newton or SQP methods.

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Last Modified By: Thomas Kloepfer
Last Update:2010-12-03
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