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Adjoint based Hessians for optimization problems in system identification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

An adjoint sensitivity based approach to determine the gradient and Hessian of cost functions for system identification is presented. The motivation is the development of a computationally efficient approach relative to the direct differentiation technique and which overcomes the challenges of the step size selection in finite difference approaches. The discrete time measurements result in discontinuities in the Lagrange multipliers. The proposed approach is illustrated on the Lorenz 63 model where part of the initial conditions and model parameters are estimated.

Original languageEnglish
Title of host publication1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages626-631
Number of pages6
ISBN (Electronic)9781509021826
DOIs
StatePublished - Oct 6 2017
Event1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 - Kohala Coast, United States
Duration: Aug 27 2017Aug 30 2017

Publication series

Name1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
Volume2017-January

Conference

Conference1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
Country/TerritoryUnited States
CityKohala Coast
Period08/27/1708/30/17

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