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Nonparametric Modeling of an Automotive Damper Based on ANN: Effect in the Control of a Semi-active Suspension

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Computational Intelligence (IJCCI 2012)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 577))

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Abstract

A model for a Magneto-Rheological (MR) damper based on Artificial Neural Networks (ANN) is proposed. The design of the ANN model is focused to get the best architecture that manages the trade-off between computing cost and performance. Experimental data provided from two MR dampers with different properties have been used to validate the performance of the proposed ANN model in comparison with the classical parametric model of Bingham. Based on the RMSE index, an average error of 7.2 % is obtained by the ANN model, by taking into account 5 experiments with 10 replicas each one; while the Bingham model has 13.8 % of error. Both model structures were used in a suspension control system for a Quarter of Vehicle (QoV) model in order to evaluate the effect of its accuracy into the design/evaluation of the control system. Simulation results show that the accurate ANN-based damper model fulfills with the control goals; while the Bingham model does not fulfill them, by concluding erroneously that the controller is insufficient and must be redesigned. The accurate MR damper model validates a realistic QoV model response compliance.

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Authors and Affiliations

  1. Tecnológico de Monterrey, Av. Garza Sada 2501, 64849, Monterrey, NL, México

    Juan C. Tudón-Martínez & Ruben Morales-Menendez

Authors
  1. Juan C. Tudón-Martínez
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  2. Ruben Morales-Menendez
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Corresponding author

Correspondence to Juan C. Tudón-Martínez .

Editor information

Editors and Affiliations

  1. University Paris-Est Créteil (UPEC), Créteil, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica, University of Coimbra, Coimbra, Portugal

    António Dourado Correia

  3. Evolutionary Systems and Biomedical Engineering Lab, Instituto Superior Tecnico IST Systems and Robotics Institute, Lisboa, Portugal

    Agostinho Rosa

  4. Polytechnic Institute of Setúbal INSTICC, Setubal, Portugal

    Joaquim Filipe

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Tudón-Martínez, J.C., Morales-Menendez, R. (2015). Nonparametric Modeling of an Automotive Damper Based on ANN: Effect in the Control of a Semi-active Suspension. In: Madani, K., Correia, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2012. Studies in Computational Intelligence, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-11271-8_19

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  • DOI: https://doi.org/10.1007/978-3-319-11271-8_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11270-1

  • Online ISBN: 978-3-319-11271-8

  • eBook Packages: EngineeringEngineering (R0)

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