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Nature-inspired heuristic paradigms for parameter estimation of control autoregressive moving average systems

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Abstract

Aim of this research is to explore the strength of evolutionary and swarm intelligence techniques for parameter identification of control autoregressive moving average (CARMA) systems. The fitness function for CARMA system identification problem is formulated through error function created in mean square sense, and learning of unknown parameters of the system model is carried out with an effective global search techniques based on genetic algorithms and particle swarm optimization algorithm. Comparative study of the design methodology is conducted from actual parameters of the systems for different values of noise variance and degree of freedom in CARMA identification model. The correctness of the proposed scheme is validated through the results of various performance measures based on mean absolute error, mean weight deviation, variance account for and Theil’s inequality coefficient, and their global variants for sufficiently large number of independent runs.

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Authors and Affiliations

  1. Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Nilore, Islamabad, 45650, Pakistan

    Ammara Mehmood

  2. Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Nilore, Islamabad, 45650, Pakistan

    Aneela Zameer

  3. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan

    Muhammad Asif Zahoor Raja & Rabia Bibi

  4. Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan

    Naveed Ishtiaq Chaudhary

  5. School of Electrical and Electronic Engineering, University of Adelaide, Adelaide, Australia

    Muhammad Saeed Aslam

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  1. Ammara Mehmood
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  2. Aneela Zameer
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  3. Muhammad Asif Zahoor Raja
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  4. Rabia Bibi
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  5. Naveed Ishtiaq Chaudhary
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  6. Muhammad Saeed Aslam
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Correspondence to Muhammad Saeed Aslam.

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Mehmood, A., Zameer, A., Raja, M.A.Z. et al. Nature-inspired heuristic paradigms for parameter estimation of control autoregressive moving average systems. Neural Comput & Applic 31, 5819–5842 (2019). https://doi.org/10.1007/s00521-018-3406-4

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