Global Identification of Kinetic Parameters via the Extent-based Incremental Approach

摘要

This contribution presents a kinetic model identification scheme that guarantees convergence to global optimality. The use of the extent-based incremental approach allows one to (i) identify each reaction individually, and (ii) reduce the number of parameters to identify via optimization to the ones that appear nonlinearly in the investigated rate law. Via Taylor expansion, the identification problem can be rearranged as a polynomial optimization problem with coefficients computed only once prior to optimization. The optimization problem is then reformulated as a convex optimization problem, namely a semidefinite program, which converges to global optimality. The approach is demonstrated via a simulated example.