Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control

Joint Authors

David Reddipogu, Joshua Sunder
Elumalai, Vinodh Kumar

Source

Journal of Control Science and Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-30

Country of Publication

Egypt

No. of Pages

16

Main Subjects

Electronic engineering
Information Technology and Computer Science

Abstract EN

This paper presents an adaptive inertia weight particle swarm optimization (AIWPSO) employed for solving the multiobjective weight optimization problem of LQR applied for the vehicle active suspension system (ASS).

To meet the competing control objectives of ASS including the ride comfort, road handling, and suspension travel, the state feedback controller design for ASS is formulated as an optimization problem and an improved PSO is employed for finding the optimal weights of the linear-quadratic regulator (LQR).

Specifically, for solving the premature convergence of the particles and imbalance between exploration and exploitation capabilities of PSO, an adaptive inertia weight that updates the velocity of the particles based on the success rate is used.

The efficacy of the AIWPSO-tuned LQR is experimentally tested on a quarter-car ASS plant using the hardware in loop (HIL) testing for an uneven road surface.

Experimental results highlight that, compared to conventional PSO-tuned LQR, the proposed scheme can significantly minimize the vehicle body acceleration due to irregular road profile while guaranteeing the minimum tire friction for passenger safety.

The ISO 2361-1 standards adopted to evaluate the ride and health criteria substantiate that the proposed scheme reduces the vibration dose value by 25.34% for a bumpy road profile.

Moreover, the cumulative power spectral density (CPSD) of vehicle body acceleration assessed in both low- and high-frequency regions manifests the significant improvement in the ride comfort.

American Psychological Association (APA)

David Reddipogu, Joshua Sunder& Elumalai, Vinodh Kumar. 2020. Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control. Journal of Control Science and Engineering،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1182732

Modern Language Association (MLA)

David Reddipogu, Joshua Sunder& Elumalai, Vinodh Kumar. Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control. Journal of Control Science and Engineering No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1182732

American Medical Association (AMA)

David Reddipogu, Joshua Sunder& Elumalai, Vinodh Kumar. Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control. Journal of Control Science and Engineering. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1182732

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1182732