Displaying similar documents to “Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with a moving measurement window”

Monitoring of chlorine concentration in drinking water distribution systems using an interval estimator

Rafał Łangowski, Mietek Brdys (2007)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper describes the design of an interval observer for the estimation of unmeasured quality state variables in drinking water distribution systems. The estimator utilizes a set bounded model of uncertainty to produce robust interval bounds on the estimated state variables of the water quality. The bounds are generated by solving two differential equations. Hence the numerical efficiency is sufficient for on-line monitoring of the water quality. The observer is applied to an exemplary...

Identification of parametric models with a priori knowledge of process properties

Krzysztof B. Janiszowski, Paweł Wnuk (2016)

International Journal of Applied Mathematics and Computer Science

Similarity:

An approach to estimation of a parametric discrete-time model of a process in the case of some a priori knowledge of the investigated process properties is presented. The knowledge of plant properties is introduced in the form of linear bounds, which can be determined for the coefficient vector of the parametric model studied. The approach yields special biased estimation of model coefficients that preserves demanded properties. A formula for estimation of the model coefficients is derived...

Nonlinear Bayesian state filtering with missing measurements and bounded noise and its application to vehicle position estimation

Lenka Pavelková (2011)

Kybernetika

Similarity:

The paper deals with parameter and state estimation and focuses on two problems that frequently occur in many practical applications: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time non-linear state space model whose uncertainties are bounded is proposed. The algorithm also copes with situations when some measurements are missing. It uses Bayesian approach and evaluates maximum a posteriori probability (MAP) estimates...

Set-membership identifiability of nonlinear models and related parameter estimation properties

Carine Jauberthie, Louise Travé-Massuyès, Nathalie Verdière (2016)

International Journal of Applied Mathematics and Computer Science

Similarity:

Identifiability guarantees that the mathematical model of a dynamic system is well defined in the sense that it maps unambiguously its parameters to the output trajectories. This paper casts identifiability in a set-membership (SM) framework and relates recently introduced properties, namely, SM-identifiability, μ-SM-identifiability, and ε-SM-identifiability, to the properties of parameter estimation problems. Soundness and ε-consistency are proposed to characterize these problems and...