Nonlinear optimal tracking with incomplete state information using finite-horizon State Dependent Riccati Equation (SDRE)

Ahmed Khamis, D. Subbaram Naidu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

In this paper, an online technique for finite-horizon nonlinear stochastic tracking problems is presented. The idea of the proposed technique is to integrate the Kalman filter algorithm and the State Dependent Riccati Equation (SDRE) technique. Unlike the ordinary methods which deal with the linearized system, this technique will estimate the unmeasured states of the nonlinear system directly, and this will make the proposed technique effective for wide range of operating points. Numerical example is given to illustrate the effectiveness of the proposed technique.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2420-2425
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Other

Other2014 American Control Conference, ACC 2014
CountryUnited States
CityPortland, OR
Period6/4/146/6/14

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Keywords

  • Kalman filtering
  • Nonlinear systems
  • Optimal control

Cite this

Khamis, A., & Naidu, D. S. (2014). Nonlinear optimal tracking with incomplete state information using finite-horizon State Dependent Riccati Equation (SDRE). In 2014 American Control Conference, ACC 2014 (pp. 2420-2425). [6858589] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2014.6858589