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Communication Dans Un Congrès Année : 2018

Local adaptive observer for linear time-varying systems with parameter-dependent state matrices

Résumé

We present an adaptive observer for linear time-varying systems whose state matrix depends on unknown parameters. We first assume that the state matrix is affine in these parameters. In this case, the proposed observer generates state and parameter estimates, which exponentially converge to the plant state and the true parameter, respectively, provided a persistence of excitation condition holds and the unknown parameters lie in a neighborhood of some known nominal values. Hence, some prior knowledge on the unknown parameters is required, but not on the state. We then modify the adaptive observer and its convergence analysis to systems whose state matrix is smooth, instead of being affine, in the unknown parameters. The convergence is approximate, and no longer exponential, in this case. An example is provided to illustrate the results, for which the required distance between the unknown parameters and their nominal values is investigated numerically.
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Dates et versions

hal-01877136 , version 1 (17-10-2018)

Identifiants

Citer

Romain Postoyan, Qinghua Zhang. Local adaptive observer for linear time-varying systems with parameter-dependent state matrices. 57th IEEE Conference on Decision and Control, CDC 2018, Dec 2018, Miami, United States. pp.4649-4554, ⟨10.1109/CDC.2018.8619470⟩. ⟨hal-01877136⟩
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