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Author: Pavel Ettler

Affiliation: COMPUREG Plzen and s.r.o., Czech Republic

Keyword(s): Parameter Estimation, Process Model, Probabilistic Distribution, Adaptive Control.

Related Ontology Subjects/Areas/Topics: Adaptive Signal Processing and Control ; Industrial Automation and Robotics ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; System Identification ; System Modeling

Abstract: Most often, the normal distribution N plays the key role in the process modelling and parameter estimation. The paper deals with 'realistic' estimation of model parameters which takes into account limitations on parameters which arise in industrial applications of the model-based adaptive control. Here the limitation of a normally distributed random variable is being modelled by specific distribution - the probabilistic mixture D. It is shown that relationship between distributions N and D coincides with properties of the generalized normal distribution G and that relations between their first and second statistical moments can be adequately approximated by G's cumulative distribution function and probability density function, respectively. The derived method is then applied to estimation of bounded parameters. In combination with the idea of parallel identification of the full and reduced models of the process, a working algorithm is derived. Performance of the algorithm is illustr ated by examples on both simulated and real data. (More)

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Paper citation in several formats:
Ettler, P. (2017). Realistic Estimation of Model Parameters. In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-263-9; ISSN 2184-2809, SciTePress, pages 527-534. DOI: 10.5220/0006395705270534

@conference{icinco17,
author={Pavel Ettler.},
title={Realistic Estimation of Model Parameters},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2017},
pages={527-534},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006395705270534},
isbn={978-989-758-263-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Realistic Estimation of Model Parameters
SN - 978-989-758-263-9
IS - 2184-2809
AU - Ettler, P.
PY - 2017
SP - 527
EP - 534
DO - 10.5220/0006395705270534
PB - SciTePress

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