Neural Computing and Applications

, Volume 31, Issue 10, pp 5819–5842 | Cite as

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

  • Ammara Mehmood
  • Aneela Zameer
  • Muhammad Asif Zahoor Raja
  • Rabia Bibi
  • Naveed Ishtiaq Chaudhary
  • Muhammad Saeed AslamEmail author
Original Article


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.


System identification Parameter estimation Evolutionary computing Genetic algorithms CARMA model 


Compliance with ethical standards

Conflict of interest

All the authors of the manuscript declared that there are no potential conflicts of interest.

Human and animal rights statements

All the authors of the manuscript declared that there is no research involving human participants and/or animal.

Informed consent

All the authors of the manuscript declared that there is no material that required informed consent.


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Department of Electrical EngineeringPakistan Institute of Engineering and Applied Sciences (PIEAS)NilorePakistan
  2. 2.Department of Computer and Information SciencesPakistan Institute of Engineering and Applied Sciences (PIEAS)NilorePakistan
  3. 3.Department of Electrical EngineeringCOMSATS Institute of Information TechnologyAttockPakistan
  4. 4.Department of Electrical EngineeringInternational Islamic UniversityIslamabadPakistan
  5. 5.School of Electrical and Electronic EngineeringUniversity of AdelaideAdelaideAustralia

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