Soft Computing

, Volume 21, Issue 14, pp 3849–3858 | Cite as

Parameter estimation of MIMO bilinear systems using a Levy shuffled frog leaping algorithm

  • Narendra Kawaria
  • Rohan Patidar
  • Nithin V. George
Methodologies and Application


Parameter identification of bilinear systems has been considered as an evolutionary computing algorithm-based optimization problem in this paper. A new Levy shuffled frog leaping algorithm (LSFLA), which is an improved version of the conventional shuffled frog leaping algorithm (SFLA), has been designed and has been applied for this parameter identification task. LSFLA offers enhanced local search behaviour in comparison with other traditional evolutionary computing algorithms. The ability of the new algorithm in accurately modeling parameters in single input single output (SISO) as well as multiple input multiple output (MIMO) has been checked using an extensive simulation study. The parameter estimation efficiency of the new scheme has been compared with that obtained using other popular evolutionary computing algorithms and the simulation study reveals the enhanced parameter identification ability of the proposed LSFLA.


Bilinear system System identification Particle swarm optimization algorithm Cuckoo search algorithm Shuffled frog leaping algorithm 



This work was supported by the Department of Science and Technology, Government of India under the INSPIRE Faculty Award Scheme (IFA-13 ENG-45).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no potential conflict of interest.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Indian Institute of Technology GandhinagarGandhinagarIndia

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