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Comfort-Oriented Control for Half-Car Semi-active Suspension Using a Model Predictive Approach

  • FAW Group Corporation
  • Harbin Institute of Technology

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

Abstract

This paper presents a controller design for magnetorheological (MR) semi-active vehicle suspensions, with the main objective of optimizing suspension performance while ensuring that the desired damping coefficients of the front and rear suspension dampers generated by the control law satisfies the physical constraints of the MR damper. To tackle these control objectives, a constrained quadratic programming problem is formulated within the framework of model predictive control (MPC). Integrated Analytic Hierarchy Process (IAHP) and Particle Swarm Optimization (PSO) algorithm are then utilized to optimize the performance of the controller. The optimal control law is determined using the GRAMPC toolbox. Simulation results based on CarSim-MATLAB cosimulations are presented to validate the effectiveness and superiority of the proposed controller compared to conventional control methods.

Original languageEnglish
Title of host publicationProceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350340488
DOIs
StatePublished - 2023
Event7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023 - Changsha, China
Duration: 27 Oct 202329 Oct 2023

Publication series

NameProceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023

Conference

Conference7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023
Country/TerritoryChina
CityChangsha
Period27/10/2329/10/23

Keywords

  • GRAMPC
  • Model predictive control
  • PSO
  • pitch motion
  • semi-active suspension

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