A new approach to constrained state estimation for discrete-time linear systems with unknown inputs

J.F. Garcia Tirado, A. Marquez-Ruiz, H. Botero Castro, F. Angulo

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3 Citations (Scopus)
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Abstract

This paper addresses the problem of estimating the state for a class of uncertain discrete-time linear systems with constraints by using an optimization-based approach. The proposed scheme uses the moving horizon estimation philosophy together with the game theoretical approach to the H∞ filtering to obtain a robust filter with constraint handling. The used approach is constructive since the proposed moving horizon estimator (MHE) results from an approximation of a type of full information estimator for uncertain discrete-time linear systems, named in short H∞-MHE and H∞-full information estimator, respectively. Sufficient conditions for the stability of the H∞-MHE are discussed for a class of uncertain discrete-time linear systems with constraints. Finally, since the H∞-MHE needs the solution of a complex minimax optimization problem at each sampling time, we propose an approximation to relax the optimization problem and hence to obtain a feasible numerical solution of the proposed filter. Simulation results show the effectiveness of the robust filter proposed.

Original languageEnglish
Pages (from-to)326–341
Number of pages16
JournalInternational Journal of Robust and Nonlinear Control
Volume28
Issue number1
DOIs
Publication statusPublished - 10 Jan 2018

Keywords

  • Constrained estimation
  • Moving horizon estimation
  • Optimization
  • Robust estimation
  • Uncertain linear systems
  • constrained estimation
  • optimization
  • robust estimation
  • moving horizon estimation
  • uncertain linear systems

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