Multi-purpose economic optimal experiment design applied to model based optimal control


  • D. Telen, B. Houska, F. Logist, J. Van Impe


  • Computers & Chemical Engineering,
    Volume 94, pages 212-220, 2016.


In contrast to classical experiment design methods, often based on alphabetic criteria, economic optimal experiment design assumes that our ultimate goal is to solve an optimization or optimal control problem. As the system parameters of physical models are in practice always estimated from measurements, they cannot be assumed to be exact. Thus, if we solve the model based optimization problem using the estimated, non-exact parameters, an inevitable loss of optimality is faced. The aim of economic optimal experiment design is precisely to plan an experiment in such a way that the expected loss of optimality in the optimization is minimized. To make economic optimal experiment design fully practical, this paper analyzes the question how to estimate parameters for multiple purposes, i.e., we consider more than one candidate objective function, but we want to take measurements and estimate the parameters before we actually decide which objective we want to minimize.



author = {D. Telen and B. Houska and F. Logist and J. Van Impe},
title = {Multi-purpose economic optimal experiment design applied to model based optimal control},
journal = {Computers & Chemical Engineering},
year = {2016},
volume = {94},
pages = {212–220}