Estimation of bounded model uncertainties
Résumé
The aim is to identify the parameter values of a given input-output model such that estimated model outputs are consistent with measured outputs of the system to be modeled. Parameter estimation based on a set-membership approach is a non-probabilistic method for characterizing the uncertainty with which each model parameter is known. In this case, the sought model is consistent with data if the estimated output domain contains measured system outputs at each instant. Dynamic linear Multi-Inputs Multi-Outputs (MIMO) models are considered in this paper. Every equation error is bounded while model parameters fluctuate inside a time-invariant domain represented by a zonotope. The proposed method helps to find the characteristics of this domain (center, shape, size) by taking into account the couplings between bounded variables of output equations in order to increase model accuracy.