Application of Artificial Fish Swarm Algorithm in LQR Control for Active Suspension

Weipeng Zhao, Liang Gu, Mingming Dong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

This paper investigates the problem of artificial fish swarm algorithm (AFSA) in LQR control of active suspension. To find the optimal solution, AFSA is used to overcome the shortcoming that the coefficients are determined based on experience in the LQR, which cannot guarantee the optimal solution. At first, the quarter car active suspension model and the road excitation model are given. Then the LQR controller and LQR controller with AFSA are designed. And at last, the simulation is conducted. Compared with the conventional LQR control, LQR controller with ASFA can concurrently improve both the ride comfort and driving control stability of vehicle.

Original languageEnglish
Title of host publicationASCC 2022 - 2022 13th Asian Control Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2406-2409
Number of pages4
ISBN (Electronic)9788993215236
DOIs
Publication statusPublished - 2022
Event13th Asian Control Conference, ASCC 2022 - Jeju, Korea, Republic of
Duration: 4 May 20227 May 2022

Publication series

NameASCC 2022 - 2022 13th Asian Control Conference, Proceedings

Conference

Conference13th Asian Control Conference, ASCC 2022
Country/TerritoryKorea, Republic of
CityJeju
Period4/05/227/05/22

Keywords

  • AFSA
  • LQR
  • active suspension
  • simulation

Fingerprint

Dive into the research topics of 'Application of Artificial Fish Swarm Algorithm in LQR Control for Active Suspension'. Together they form a unique fingerprint.

Cite this