Model error compensation for observer design

We consider the state and disturbance estimation problem for a linear system with uncertainties as additive deterministic disturbances. Instead of attempting to minimize the effects of the disturbance as in the robust filters or to decouple the disturbance as in the unknown input observers, it is pr...

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Bibliographic Details
Published inInternational journal of control Vol. 69; no. 2; pp. 329 - 345
Main Authors Tu, Jay F., Stein, Jeffrey L.
Format Journal Article
LanguageEnglish
Published London Taylor & Francis Group 01.01.1998
Taylor & Francis
Subjects
Applied sciences
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
Signal and communications theory
Signal, noise
Telecommunications and information theory
Linear system
Perturbation
State estimation
Compensator
Observer
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Summary:We consider the state and disturbance estimation problem for a linear system with uncertainties as additive deterministic disturbances. Instead of attempting to minimize the effects of the disturbance as in the robust filters or to decouple the disturbance as in the unknown input observers, it is proposed to estimate the disturbance and to use it to reduce the model error and thus to improve the state estimation. This technique is denoted as model error compensator (MEC). Sufficient conditions for achieving bounded disturbance estimation error are presented. These conditions are different from those required in the unknown input observers and the robust filter for state estimation only. In addition, no differentiation of the measured signals is required. This paper also discusses how existing state observers can be used with the MEC as a two-step observer design strategy.
ISSN:0020-7179
1366-5820
DOI:10.1080/002071798222875