Estimation of Viscous Friction Parameters in Acrobot

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00184561" target="_blank" >RIV/68407700:21230/11:00184561 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Estimation of Viscous Friction Parameters in Acrobot

Popis výsledku v původním jazyce

This paper deals with estimation of coefficients of viscous friction for a model of an acrobot. The acrobot represents an underactuated nonlinear dynamic system, where typically not all states are measurable. Moreover effect of noise corruption on remaining measured states is often non negligible. However, except for friction coefficient, all remaining parameters of the model can usually be measured directly. To overcome mentioned difficulties and to take advantage of abundant prior knowledge, we applied hybrid extended Kalman filter to this task. Using Monte Carlo (MC) simulations we approximated probability density functions of friction coefficients estimate and showed that the bias and variance of the estimate can be controlled by properly designedexperiment.

Název v anglickém jazyce

Estimation of Viscous Friction Parameters in Acrobot

Popis výsledku anglicky

This paper deals with estimation of coefficients of viscous friction for a model of an acrobot. The acrobot represents an underactuated nonlinear dynamic system, where typically not all states are measurable. Moreover effect of noise corruption on remaining measured states is often non negligible. However, except for friction coefficient, all remaining parameters of the model can usually be measured directly. To overcome mentioned difficulties and to take advantage of abundant prior knowledge, we applied hybrid extended Kalman filter to this task. Using Monte Carlo (MC) simulations we approximated probability density functions of friction coefficients estimate and showed that the bias and variance of the estimate can be controlled by properly designedexperiment.

Druh

O - Ostatní výsledky

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/GAP103%2F10%2F0628" target="_blank" >GAP103/10/0628: Semidefinitní programování po nelineární dynamické systémy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů