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Design of momentum fractional LMS for Hammerstein nonlinear system identification with application to electrically stimulated muscle model

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Abstract.

Fractional calculus extends the scope of adaptive algorithms supporting the design of novel fractional methods that outperform standard strategies in various applications arising in applied physics and engineering. In this study, a momentum fractional least-mean-square (M-FLMS) algorithm for nonlinear system identification using a first and fractional-order gradient information is proposed. The M-FLMS avoids being trapped in local minima and provides faster convergence than the standard FLMS. The convergence and complexity analysis of the M-FLMS are given along with simulation results of a benchmark nonlinear system identification problem. The M-FLMS accuracy is verified through a parameter estimation problem for a nonlinear Hammerstein structure, modeling an electrically stimulated muscle (ESM) for rehabilitation of paralyzed muscles. The proposed method is studied in detail for different levels of noise variance, fractional orders and proportion of gradients used in the current update.

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Authors and Affiliations

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

    Naveed Ishtiaq Chaudhary & Syed Zubair

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

    Muhammad Saeed Aslam

  3. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock, Pakistan

    Muhammad Asif Zahoor Raja

  4. Department of Electrical Engineering, Institute of Engineering, Polytechnic of Porto, Porto, Portugal

    J. A. Tenreiro Machado

Authors
  1. Naveed Ishtiaq Chaudhary
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  2. Syed Zubair
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  3. Muhammad Saeed Aslam
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  4. Muhammad Asif Zahoor Raja
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  5. J. A. Tenreiro Machado
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Correspondence to Muhammad Saeed Aslam.

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Chaudhary, N.I., Zubair, S., Aslam, M.S. et al. Design of momentum fractional LMS for Hammerstein nonlinear system identification with application to electrically stimulated muscle model. Eur. Phys. J. Plus 134, 407 (2019). https://doi.org/10.1140/epjp/i2019-12785-8

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  • DOI: https://doi.org/10.1140/epjp/i2019-12785-8

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