Astrophysical expedition: Transit search heuristics for fractional Hammerstein control autoregressive models

Author:

Altaf Faisal1ORCID,Chang Ching-Lung2ORCID,Chaudhary Naveed Ishtiaq3ORCID,Ali Khan Taimoor4ORCID,Khan Zeshan Aslam5ORCID,Shu Chi-Min6ORCID,Raja Muhammad Asif Zahoor3ORCID

Affiliation:

1. Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. China

2. Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. China

3. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. China

4. International Graduate School of Artificial Intelligence, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. China

5. Department of Electrical and Computer Engineering, International Islamic University, Islamabad 44000, Islamabad Capital Territory, Pakistan

6. Department of Safety, Health and Environmental Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R. O. China

Abstract

This study presents an astrophysics-inspired transit search optimization (TSO) algorithm based on exoplanet search divided into five phases: galaxy phase, star phase, transit phase, neighbor phase and exploitation phase for effective parameter estimation of fractional Hammerstein control autoregressive (Fr-HCAR) systems. Various physical phenomena and real processes can be modeled with Fr-HCAR systems and estimating the Fr-HCAR parameters becomes a vital task. The mean-square error (MSE)-based criterion function is developed, and efficacy of the TSO for Fr-HCAR identification is deeply analyzed for different fractional orders, disturbance levels and degrees of freedom. The TSO remained accurate, convergent, robust and stable for all variations in Fr-HCAR but the accuracy level degrades a little bit for high disturbance and increased degrees of freedom. The reliability and trustworthiness of the TSO for Fr-HCAR identification are endorsed through statistical analyses conducted on sufficient autonomous executions of the scheme.

Publisher

World Scientific Pub Co Pte Ltd

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