Author:

Keywords:

OPTIMAL EXPERIMENTAL-DESIGN, PARAMETER-ESTIMATION, BATCH, BIOPROCESSES, SYSTEMS, Science & Technology, Technology, Engineering, Chemical, Engineering, FED-BATCH FERMENTATION, 03 Chemical Sciences, 09 Engineering, Chemical Engineering, 34 Chemical sciences, 40 Engineering

Abstract:

The problem of optimal experimental design (OED) for parameter estimation of nonlinear dynamic systems is considered. It is shown how this problem can be formulated as a dynamic optimization (optimal control) problem where the performance index is usually a scalar function of the Fisher information matrix. Numerical solutions can be obtained using direct methods, which transform the original problem into a nonlinear programming (NLP) problem via parametrizations. However, because of the frequent nonsmoothness of the cost functions, the use of gradient-based methods to solve this NLP might lead to local solutions. Stochastic methods of global optimization are suggested as robust alternatives. A case study considering the OED for parameter estimation in a fed-batch bioreactor is used to illustrate the performance and advantages of two selected stochastic algorithms.