AAC 2019 Paper Abstract

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Paper TuAT2.6

MURALI MADHAVAN RATHAI, KARTHIK (GIPSA Lab - University of Grenoble, Alpes, Grenoble, France), Alamir, Mazen (Gipsa-Lab (CNRS-University of Grenoble)), Sename, Olivier (Grenoble Institute of Technology / GIPSA-Lab)

Experimental Implementation of Model Predictive Control Scheme for Control of Semi-Active Suspension System

Scheduled for presentation during the Invited Session "Vehicle Suspension Control I" (TuAT2), Tuesday, June 25, 2019, 12:10−12:30, Chenonceau

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 25, 2024

Keywords Active Chassis Systems: Brake, Steering, Suspension Systems, Plant Modelling and System Identification, Rapid Control Prototyping

Abstract

In this paper, a model predictive control (MPC) scheme is developed and experimentally validated for control of a quarter car system equipped with semi-active (SA) suspension system, which is stationed on the INOVE test platform. The work can be described in two folds which are a) parametric modelling of Electro-Rheological (ER) damper based SA suspension system (ER-SA) and b) implementation of MPC with discretized set of inputs, which in this case are the set of duty cycle (DC) dependent pulse width modulation (PWM) signals that operates the ER-SA suspension system. In the former work, a phenomenological parametric damper model is utilized to describe the ER damper's dynamic input/output characteristics by virtue of non-linear least squares (NLS) data fitting method. The latter method utilizes this model into the MPC framework for control of the quarter car system. The MPC controller was practically implemented on the INOVE test platform and results display better performance of the MPC controller in comparison with passive damping and modified Skyhook controller.

 

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