Brief paper: A generalized framework for robust nonlinear H∞ filtering of Lipschitz descriptor systems with parametric and nonlinear uncertainties

  • Authors:
  • Masoud Abbaszadeh;Horacio J. Marquez

  • Affiliations:
  • United Technologies Research Center, East Hartford, CT, 06108, USA;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2V4, Canada

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2012

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Abstract

In this paper, a generalized robust nonlinear H"~ filtering method is proposed for a class of Lipschitz descriptor systems, in which the nonlinearities appear both in the state and measured output equations. The system is assumed to have norm-bounded uncertainties in the realization matrices as well as nonlinear uncertainties. We synthesize the H"~ filter through semidefinite programming and strict LMIs. The admissible Lipschitz constants of the nonlinear functions are maximized through LMI optimization. The resulting H"~ filter guarantees asymptotic stability of the estimation error dynamics with prespecified disturbance attenuation level and is robust against time-varying parametric uncertainties as well as Lipschitz nonlinear additive uncertainty. Explicit bound on the tolerable nonlinear uncertainty is derived based on a norm-wise robustness analysis.