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An improved search space resizing method for model identification by Standard Genetic Algorithm

Rajarathinam, K and Gomm, JB and Yu, DL and Abdelhadi, AS (2015) An improved search space resizing method for model identification by Standard Genetic Algorithm. In: 2015 21st International Conference on Automation and Computing: Automation, Computing and Manufacturing for New Economic Growth, ICAC 2015 . (21st International Conference on Automation and Computing, 11th - 12th September 2015, University of Strathclyde, Glasgow, UK).

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Abstract

.In this paper, a new improved search space boundary resizing method for an optimal model's parameter identification by Standard Genetic Algorithms (SGAs) is proposed and demonstrated. The premature convergence to local minima, as a result of search space boundary constraints, is a key consideration in the application of SGAs. The new method improves the convergence to global optima by resizing or extending the upper and lower search boundaries. The resizing of search space boundaries involves two processes, first, an identification of initial value by approximating the dynamic response period and desired settling time. Second, a boundary resizing method derived from the initial search space value. These processes brought the elite groups within feasible boundary regions by consecutive execution and enhanced the SGAs in locating the optimal model's parameters for the identified transfer function. This new method is applied and examined on two processes, a third order transfer function model with and without random disturbance and raw data of excess oxygen. The simulation results assured the new improved search space resizing method's efficiency and flexibility in assisting SGAs to locate optimal transfer function model parameters in their explorations. © 2015 Chinese Automation and Computing Society in the UK - CACS

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: Electronics and Electrical Engineering
Publisher: Chinese Automation and Computing Society in the UK CACS
Date Deposited: 14 Sep 2016 11:22
Last Modified: 14 Sep 2016 11:22
DOI or Identification number: 10.1109/IConAC.2015.7313940
URI: http://researchonline.ljmu.ac.uk/id/eprint/4078

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