Intelligent controllers for vechicle suspension system using magnetorheological damper

Semi-active suspension control with magnetorheological (MR) damper is one of the most fascinating systems being studied in improving the vehicle ride comfort. This study aims to investigate the development of intelligent controllers for vehicle suspension system using MR damper, namely, the proporti...

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Main Author: Ab. Talib, Mat Hussin
Format: Thesis
Language:English
Published: 2017
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Online Access:http://eprints.utm.my/id/eprint/79136/1/MatHussinAbTalibPFKM2017.pdf
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spelling my-utm-ep.791362018-09-30T08:23:12Z Intelligent controllers for vechicle suspension system using magnetorheological damper 2017 Ab. Talib, Mat Hussin TJ Mechanical engineering and machinery Semi-active suspension control with magnetorheological (MR) damper is one of the most fascinating systems being studied in improving the vehicle ride comfort. This study aims to investigate the development of intelligent controllers for vehicle suspension system using MR damper, namely, the proportional-integral-derivative (PID) and fuzzy logic (FL) controllers optimized using particle swarm optimization (PSO), firefly algorithm (FA) and advanced firefly algorithm (AFA). Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. The PSO and FA are among of the evolutionary algorithms which have been studied in this research. Nevertheless, the weakness of FA such as getting trapped into several local minima is an attractive area that has been focused more as a possible improvement during the evolutionary process. Thus, a new algorithm based on the improvement of the original FA was introduced to improve the solution quality of the FA. This algorithm is called advanced firefly algorithm. A parametric modelling technique known as Spencer model was proposed and employed to compute the dynamic behaviour of the MR damper system. The Spencer model was experimentally validated and conducted to capture the behaviour of the Lord RD-1005-3 MR damper with the same excitation input. A simulation of a semi-active suspension system was developed within MATLAB Simulink environment. The effectiveness of all control schemes were investigated in two major issues, namely the ability of the controller to reject the unwanted motion of the vehicle and to overcome the damping constraints. The result indicates that, the PID-AFA control scheme is more superior as compared to the PID-PSO, PID-FA, FL-PSO, FL-FA, FL-AFA and passive system with up to 27.1% and 19.1% reduction for sprung mass acceleration and sprung mass displacement, respectively. Finally, the performance of the proposed intelligent control schemes which are implemented experimentally on the developed quarter vehicle suspension test rig shows a good agreement with the results of the simulation study. The proposed control scheme of PID-AFA has reduced the sprung mass acceleration and sprung mass displacement over the FL-AFA and passive system up to 28.21% and 16.9%, respectively. 2017 Thesis http://eprints.utm.my/id/eprint/79136/ http://eprints.utm.my/id/eprint/79136/1/MatHussinAbTalibPFKM2017.pdf application/pdf en public phd doctoral Universiti Teknologi Malaysia, Faculty of Mechanical Faculty of Mechanical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Ab. Talib, Mat Hussin
Intelligent controllers for vechicle suspension system using magnetorheological damper
description Semi-active suspension control with magnetorheological (MR) damper is one of the most fascinating systems being studied in improving the vehicle ride comfort. This study aims to investigate the development of intelligent controllers for vehicle suspension system using MR damper, namely, the proportional-integral-derivative (PID) and fuzzy logic (FL) controllers optimized using particle swarm optimization (PSO), firefly algorithm (FA) and advanced firefly algorithm (AFA). Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. The PSO and FA are among of the evolutionary algorithms which have been studied in this research. Nevertheless, the weakness of FA such as getting trapped into several local minima is an attractive area that has been focused more as a possible improvement during the evolutionary process. Thus, a new algorithm based on the improvement of the original FA was introduced to improve the solution quality of the FA. This algorithm is called advanced firefly algorithm. A parametric modelling technique known as Spencer model was proposed and employed to compute the dynamic behaviour of the MR damper system. The Spencer model was experimentally validated and conducted to capture the behaviour of the Lord RD-1005-3 MR damper with the same excitation input. A simulation of a semi-active suspension system was developed within MATLAB Simulink environment. The effectiveness of all control schemes were investigated in two major issues, namely the ability of the controller to reject the unwanted motion of the vehicle and to overcome the damping constraints. The result indicates that, the PID-AFA control scheme is more superior as compared to the PID-PSO, PID-FA, FL-PSO, FL-FA, FL-AFA and passive system with up to 27.1% and 19.1% reduction for sprung mass acceleration and sprung mass displacement, respectively. Finally, the performance of the proposed intelligent control schemes which are implemented experimentally on the developed quarter vehicle suspension test rig shows a good agreement with the results of the simulation study. The proposed control scheme of PID-AFA has reduced the sprung mass acceleration and sprung mass displacement over the FL-AFA and passive system up to 28.21% and 16.9%, respectively.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ab. Talib, Mat Hussin
author_facet Ab. Talib, Mat Hussin
author_sort Ab. Talib, Mat Hussin
title Intelligent controllers for vechicle suspension system using magnetorheological damper
title_short Intelligent controllers for vechicle suspension system using magnetorheological damper
title_full Intelligent controllers for vechicle suspension system using magnetorheological damper
title_fullStr Intelligent controllers for vechicle suspension system using magnetorheological damper
title_full_unstemmed Intelligent controllers for vechicle suspension system using magnetorheological damper
title_sort intelligent controllers for vechicle suspension system using magnetorheological damper
granting_institution Universiti Teknologi Malaysia, Faculty of Mechanical
granting_department Faculty of Mechanical Engineering
publishDate 2017
url http://eprints.utm.my/id/eprint/79136/1/MatHussinAbTalibPFKM2017.pdf
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