Title: A vehicle suspension system based on Kalman filtering model predictive control algorithm

Authors: Akshaya Kumar Patra

Addresses: Department of Electrical and Electronics Engineering, ITER, Siksha 'O' Anusandhan University, Bhubaneswar, 751030, Odisha, India

Abstract: The aim of this manuscript is to formulate a Kalman filtering model predictive controller (KFMPC) for a vehicle suspension system (VSS) to enhance the ride luxury by retaining the stuns because of an unpleasant and crooked road. For the formulation of the KFMPC, a 4th order state-space structure of the VSS is deliberated. In this strategy, the conventional model predictive controller (CMPC) is redesigned by use of the Kalman filter to upgrade the control execution. The approval of the upgraded control execution of KFMPC is set up by comparative outcome examination with other well-known control strategies. The relative outcomes obviously reveal the better execution of the recommended strategy to monitor the VSS dynamics inside a steady range as for the accuracy, stability, and robustness.

Keywords: vehicle suspension system; VSS; oscillation; Kalman filter; model predictive control.

DOI: 10.1504/IJAMECHS.2021.116455

International Journal of Advanced Mechatronic Systems, 2021 Vol.9 No.2, pp.55 - 65

Received: 20 May 2020
Accepted: 23 Sep 2020

Published online: 14 Jul 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article