Multi-objective Order Reduction Problem Solving with Restart Meta-heuristic Implementation

Ivan Ryzhikov, Christina Brester, Eugene Semenkin

2017

Abstract

An order reduction problem for linear time invariant models brought to the multi-objective optimization problem is considered. Each criterion is multi-extremum and complex, requires an efficient tool for estimating the parameters of the lower order system and characterizes the model adequacy for the unit-step and Dirac function inputs. A common problem definition is to estimate the lower order model coefficients by minimizing the distance between the output of this model and the initial one. We propose an evolution-based multi-objective stochastic optimization algorithm with a restart operator implemented. The algorithm performance was estimated on two order reduction problems for a single input-single output system and a multiple input-multiple output one. The effectiveness of the algorithm increased sufficiently after implementing a meta-heuristic restart operator. It is shown that the proposed approach is comparable to other approaches, but allows a Pareto-front approximation to be found and not just a single solution.

Paper Citation

in Harvard Style

Ryzhikov I., Brester C. and Semenkin E. (2017). Multi-objective Order Reduction Problem Solving with Restart Meta-heuristic Implementation . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 270-278. DOI: 10.5220/0006431002700278

in Bibtex Style

@conference{icinco17,
author={Ivan Ryzhikov and Christina Brester and Eugene Semenkin},
title={Multi-objective Order Reduction Problem Solving with Restart Meta-heuristic Implementation},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={270-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006431002700278},
isbn={978-989-758-263-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Multi-objective Order Reduction Problem Solving with Restart Meta-heuristic Implementation
SN - 978-989-758-263-9
AU - Ryzhikov I.
AU - Brester C.
AU - Semenkin E.
PY - 2017
SP - 270
EP - 278
DO - 10.5220/0006431002700278