Tube-based model reference adaptive control for vibration suppression of active suspension systems

Yashar Mousavi , Alireza Alfi, Ibrahim Beklan Kucukdemiral, Afef Fekih*

*Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

1 Citation (Scopus)
31 Downloads (Pure)


Active suspension systems are critical components that play a decisive role in improving ride comfort and maneuverability of vehicles. However, inevitable road disturbances and parameter uncertainties, such as variation of the payload mass and some suspension components, lead to control performance deterioration. This paper synthesizes a tube- based model reference adaptive control (T-MRAC) scheme to enhance the suspension performance of active vehicle suspension systems. The proposed paradigm substitutes the single trajectory generated by the reference model in classical adaptive design with an optimal trajectory with a tube reference model. To illustrate the feasibility of the developed control scheme, it is applied to enhance the vertical dynamic performance of a quarter-car active suspension system with parameter uncertainties and road disturbances. By using the developed control approach, the ride comfort quality is improved, and the vehicle handling and suspension safety objectives are fulfilled in different road situations. Comparative simulation results validate the efficiency of the proposed control strategy in providing desirable vibration suppression performance with less control effort and maintaining the relative suspension deflection and relative tire force constraints within the permissible ranges.
Original languageEnglish
Pages (from-to)728-731
Number of pages4
JournalIEEE/CAA Journal of Automatica Sinica
Issue number4
Early online date9 Mar 2022
Publication statusPublished - Apr 2022


  • tube-based model reference adaptive control, quarter-car active suspension system, vibration suppression, stability analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering


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