Joint state and parameter estimation for discrete-time polytopic linear parameter-varying systems

H.P.G.J. Beelen, M.C.F. Donkers

Onderzoeksoutput: Bijdrage aan tijdschriftCongresartikelpeer review

2 Citaten (Scopus)
8 Downloads (Pure)


Linear parameter-varying systems are very suitable for modelling nonlinear systems, since well-established methods from the linear-systems domain can be applied. Knowledge about the scheduling parameter is an important condition in this modelling framework. In case this parameter is not known, joint state and parameter-estimation methods can be employed, e.g., using interacting multiple-model estimation methods, or using an extended Kalman filter. However, these methods cannot be directly used in case the parameters lie in a polytopic set. Furthermore, these existing methods require tuning in order to have convergence and stability. In this paper, we propose to solve the joint-estimation problem in a two-step, Dual Estimation approach, where we first solve the parameter-estimation problem by solving a constrained optimisation problem in a recursive manner and secondly, employ a robust polytopic observer design for state estimation. Simulations show that our novel method outperforms the existing joint-estimation methods and is a promising first step for further research.

Originele taal-2Engels
Pagina's (van-tot)9778-9783
Aantal pagina's6
Nummer van het tijdschrift1
StatusGepubliceerd - 1 jul. 2017
Evenement20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress) - Toulouse, Frankrijk
Duur: 9 jul. 201714 jul. 2017
Congresnummer: 20


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