A novel single parent mating technique in genetic algorithm for discrete - time system identification
System identification is concerned with the construction of a mathematical model based on given input and output data to represent the dynamical behaviour of a system. As a step in system identification, model structure selection is a step where a model perceived as adequate system representation is...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Semarak Ilmu Publishing
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/27526/2/003120306202411425840.PDF http://eprints.utem.edu.my/id/eprint/27526/ https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/view/4185/4377 |
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| Summary: | System identification is concerned with the construction of a mathematical model based on given input and output data to represent the dynamical behaviour of a system. As a step in system identification, model structure selection is a step where a model perceived as adequate system representation is selected. A typical rule is that the model must have a good balance between parsimony and accuracy in estimating a dynamic system. As a popular search method, genetic algorithm (GA) is used for selecting a model structure. However, the optimality of the final model depends much on the optimality of GA. This paper introduces a novel mating technique in GA based on the chromosome structure of the parents such that a single parent is sufficient in achieving mating that demonstrates high exploration capability. In investigating this, four systems of linear and nonlinear classes were simulated to generate discrete-time sets of data i.e. later used for identification. The outcome shows that GA incorporated with the mating technique within 10%-20% of the population size is able to find optimal models quicker than the traditional GA. |
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