Integration of Bilinear Systems and Neural Networks for Designing Nonlinear Semi-Active Suspensions

Antonio Moran, Tomohiro Hasegawa, Masao Nagai

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper presents a new design method of semi-active suspensions based on the integration of neural networks and bilinear systems. It is known that semi-active suspensions with ideal linear components have a bilinear structure. However actual semi-active suspensions with nonlinear components have an structure which is not purelv bilinear. In order to improve the performance of semi-active suspensions, neural networks and bilinear systems are integrated and used Tor the identification and optimal control of nonlinear semi-active suspensions. The validity and applicability of the proposed method are analyzed and verified theoretically and experimentally using a semi-active suspension model equipped with piezoelectric actuators.

Original languageEnglish
Pages (from-to)295-300
Number of pages6
JournalJournal of Robotics and Mechatronics
Volume7
Issue number4
DOIs
StatePublished - Aug 1995
Externally publishedYes

Keywords

  • Neural networks
  • Nonlinear identification
  • Nonlinear optimal control
  • Ride quality
  • Semi-active suspension
  • Vibration isolation

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