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Direct Multiple Shooting for Nonlinear Optimum Experimental Design

  • Dennis Janka
  • Stefan Körkel
  • Hans Georg Bock
Conference paper
Part of the Contributions in Mathematical and Computational Sciences book series (CMCS, volume 9)

Abstract

Optimum experimental design (OED) for parameter identification has become a key technique in the model validation process for dynamical systems. This paper deals with optimum experimental design for systems modelled by differential-algebraic equations. We show how to formulate OED as a nonstandard nonlinear optimal control problem. The direct multiple shooting method is a state of the art method for the solution of standard optimal control problems that leads to structured nonlinear programs. We present two possibilities how to adapt direct multiple shooting to OED by introducing additional variables and constraints. We highlight special structures in the constraint and objective derivatives whose evaluation is usually the bottleneck when solving dynamic optimization problems by multiple shooting. We have implemented a structure exploiting algorithm that takes all these structures into account. Two benchmark examples show the efficiency of the new algorithm.

Keywords

Optimal Control Problem Multiple Shooting Parameter Estimation Problem Path Constraint Optimum Experimental Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dennis Janka
    • 1
  • Stefan Körkel
    • 1
  • Hans Georg Bock
    • 1
  1. 1.Interdisciplinary Center for Scientific ComputingHeidelberg UniversityHeidelbergGermany

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