The memetic ant colony optimization with directional derivatives simplex algorithm for time delays identification

Authors:
Janusz P. Papliński
Affiliations:
Department of Control and Measurement, West Pomeranian University of Technology, Szczecin, Poland
Venue:
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Year:
2011

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Abstract

The identification of time delay in the linear plant is important tasks. Most of the conventional identification techniques, such as those based on least mean-squares, are essentially gradient-guided local search techniques and they require a smooth search space or a differentiable performance index. New possibility in this field is opened by an application of the hybrid Ant Colony Optimization (ACO) with local optimization algorithm. The Directional Derivatives Simplex (DDS) as a local optimization algorithm is proposed in the paper and used in the memetic ACODDS method. The ACODDS algorithm is compared with ACO and a classical methods: Global Separable Nonlinear Least Squares (GSNLS). The obtained results suggest that the proposed method performs well in estimating the model parameters.