Appraisal of Takagi–Sugeno type neuro-fuzzy network system with a modified differential evolution method to predict nonlinear wheel dynamics caused by road irregularities

Hamid Taghavifar, Asad Modarres Motlagh, Aref Mardani, Ali Hassanpour, Ashkan Haji Hosseinloo, Leyla Taghavifa, Chongfeng Wei

Research output: Contribution to journalArticle

3 Citations (Scopus)
11 Downloads (Pure)


Wheel dynamics play a substantial role in traversing and controlling the vehicle, braking, ride comfort, steering, and maneuvering. The transient wheel dynamics are difficult to be ascertained in tire–obstacle contact condition. To this end, a single-wheel testing rig was utilized in a soil bin facility for provision of a controlled experimental medium. Differently manufactured obstacles (triangular and Gaussian shaped geometries) were employed at different obstacle heights, wheel loads, tire slippages and forward speeds to measure the forces induced at vertical and horizontal directions at tire–obstacle contact interface. A new Takagi–Sugeno type neuro-fuzzy network system with a modified Differential Evolution (DE) method was used to model wheel dynamics caused by road irregularities. DE is a robust optimization technique for complex and stochastic algorithms with ever expanding applications in real-world problems. It was revealed that the new proposed model can be served as a functional alternative to classical modeling tools for the prediction of nonlinear wheel dynamics.
Original languageEnglish
Pages (from-to)211–220
Number of pages10
Issue number2
Publication statusPublished - 28 Jun 2016
Externally publishedYes


Bibliographical note

Copyright © 2019 The Author(s). Published by VGTU Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


  • fuzzy system
  • wheel dynamics
  • obstacle
  • off-road
  • tire–obstacle contact
  • modeling

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