Modified Evolutionary Strategies Algorithm in Linear Dynamic System Identification

Ivan Ryzhikov, Eugene Semenkin

Abstract

The approach to dynamic systems modelling in the form of the linear differential equation that uses only the system output and the control sample is presented. To develop a linear dynamic model as an ordinary differential equation we need to know the structure of differential equation and its order, so then it would be possible to identify parameters. It is common that measurements of the system output are distorted with a noise. In case of the non-uniform sample we would need a special output function approximation approach so the unit step function can be estimated. The dynamic system identification with an ordinary linear differential equation allows solving different control tasks, determining the system state with another control function.

References

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Paper Citation


in Harvard Style

Ryzhikov I. and Semenkin E. (2012). Modified Evolutionary Strategies Algorithm in Linear Dynamic System Identification . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 618-621. DOI: 10.5220/0004044706180621


in Bibtex Style

@conference{icinco12,
author={Ivan Ryzhikov and Eugene Semenkin},
title={Modified Evolutionary Strategies Algorithm in Linear Dynamic System Identification},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2012},
pages={618-621},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004044706180621},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Modified Evolutionary Strategies Algorithm in Linear Dynamic System Identification
SN - 978-989-8565-21-1
AU - Ryzhikov I.
AU - Semenkin E.
PY - 2012
SP - 618
EP - 621
DO - 10.5220/0004044706180621