Design of a non-linear hybrid car suspension system using neural networks

Konstantinos Spentzas, Stratis A. Kanarachos

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

A methodology for the design of active/hybrid car suspension systems with the goal to maximize passenger comfort (minimization of passenger acceleration) is presented. For this reason, a neural network (NN) controller is proposed, who corresponds to a Taylor series approximation of the (unknown) non-linear control function and the NN is due to the numerous local minima trained using a semi-stochastic parameter optimization method. Two cases A and B (continuous and discontinuous operation) are investigated and numerical examples illustrate the design methodology.

Original languageEnglish
Pages (from-to)369-378
Number of pages10
JournalMathematics and Computers in Simulation
Volume60
Issue number3-5
Early online date20 Mar 2002
DOIs
Publication statusPublished - 30 Sept 2002
Externally publishedYes

Keywords

  • Hybrid car suspension
  • Neural networks
  • Semi-stochastic optimization

ASJC Scopus subject areas

  • Information Systems and Management
  • Control and Systems Engineering
  • Applied Mathematics
  • Computational Mathematics
  • Modelling and Simulation

Fingerprint

Dive into the research topics of 'Design of a non-linear hybrid car suspension system using neural networks'. Together they form a unique fingerprint.

Cite this