Design of fractional-order hammerstein control auto-regressive model for heat exchanger system identification: Treatise on fuzzy-evolutionary computing

Ammara Mehmood, Muhammad Asif Zahoor Raja and Brett Ninness

Chaos, Solitons & Fractals, 2024, vol. 181, issue C

Abstract: Parameter estimation of nonlinear dynamical Hammerstein processes is a renowned stiff optimization problem with extensive applications in the design, robustness and stability analysis. Introduction of the fractional calculus theories and concepts further escalates the competency of accurate modelling of Hammerstein system but at the cost of increase in the stiffness of parameter estimation and complexity. This study deals with a presentation of new design of fractional-order nonlinear Hammerstein control auto-regressive (FO-NHCAR) model for heat exchanger system by introducing fractional derivative of polynomial based transformation operator in linear dynamic block. The system identification problem of FO-NHCAR heat exchanger system is constructed by exploiting approximation theory in mean squared error sense taken between the actual and estimated responses. Exhaustive simulations are conducted via well-known global search efficacy of the fuzzy-evolutionary computing paradigm i.e., fuzzy-genetic algorithms (GAs), for FO-NHCAR heat exchanger model by variation in signal to noise ratios, model's degrees of freedom, fractional orders, and Hammerstein kernels. The parameter vectors of FO-NHCAR models are identified consistently with the fuzzy-GAs for various noisy environments with negligible proximity error. Results comparison on rigorous statistical analysis further endorse the efficient, accurate, robust and stable performance of fuzzy- GAs for estimation of FO-NHCAR heat exchanger system parameters.

Keywords: Parameter estimation; Heat exchanger system; Fractional-order Hammerstein systems; Fuzzy-genetic algorithms (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077924001954
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924001954

DOI: 10.1016/j.chaos.2024.114644

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().