Intelligent active force control of a vehicle suspension system

Active suspension control aims to suppress the undesirable vibration and other loading effects and should provide improvements in term of passenger comfort. This study deals with the design and implementation of robust active force control (AFC)-based schemes that incorporates artificial intelligenc...

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Main Author: Priyandoko, Gigih
Format: Thesis
Language:English
Published: 2009
Subjects:
Online Access:http://eprints.utm.my/id/eprint/13618/1/GigihPriyandokoPFKM2009.pdf
http://eprints.utm.my/id/eprint/13618/
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spelling my.utm.136182018-06-26T07:50:27Z http://eprints.utm.my/id/eprint/13618/ Intelligent active force control of a vehicle suspension system Priyandoko, Gigih TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Active suspension control aims to suppress the undesirable vibration and other loading effects and should provide improvements in term of passenger comfort. This study deals with the design and implementation of robust active force control (AFC)-based schemes that incorporates artificial intelligence techniques plus a number of feedback control strategies applied to a vehicle suspension system. The overall proposed control system essentially comprises four feedback control loops, namely, an innermost loop for force tracking of the pneumatic actuator using a proportional-integral controller, two intermediate loops applying the skyhook and AFC strategy for the compensation of the disturbances and an outermost loop for the computation of the desired force for the actuator using a proportional-integral-derivative controller. Adaptive neural network and adaptive fuzzy were proposed and employed to compute the inverse dynamics of the nonlinear pneumatic actuator and estimated mass of the system within the AFC loop. The integration of all the interrelated elements leads to the formation of two main proposed schemes known as the Skyhook Adaptive Fuzzy Active Force Control and Skyhook Adaptive Neuro Active Force Control. The suspension system was modelled based on a two degree-of-freedom quarter car configuration. A number of road profiles were also modelled as the main disturbance elements to evaluate the system robustness and vehicle dynamic performance related to ride comfort. Simulation results both in time and frequency domains demonstrate the effectiveness of the proposed AFC-based schemes in countering the disturbances and other loading conditions. The schemes show evidence of at least 33.9% improvement in performance over the passive suspension. This is complemented by an experimental study on a developed full scale quarter car suspension test rig which shows a very good agreement with the simulation counterpart. 2009 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/13618/1/GigihPriyandokoPFKM2009.pdf Priyandoko, Gigih (2009) Intelligent active force control of a vehicle suspension system. PhD thesis, Universiti Teknologi Malaysia, Fakulti Kejuruteraan Mekanikal.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
Priyandoko, Gigih
Intelligent active force control of a vehicle suspension system
description Active suspension control aims to suppress the undesirable vibration and other loading effects and should provide improvements in term of passenger comfort. This study deals with the design and implementation of robust active force control (AFC)-based schemes that incorporates artificial intelligence techniques plus a number of feedback control strategies applied to a vehicle suspension system. The overall proposed control system essentially comprises four feedback control loops, namely, an innermost loop for force tracking of the pneumatic actuator using a proportional-integral controller, two intermediate loops applying the skyhook and AFC strategy for the compensation of the disturbances and an outermost loop for the computation of the desired force for the actuator using a proportional-integral-derivative controller. Adaptive neural network and adaptive fuzzy were proposed and employed to compute the inverse dynamics of the nonlinear pneumatic actuator and estimated mass of the system within the AFC loop. The integration of all the interrelated elements leads to the formation of two main proposed schemes known as the Skyhook Adaptive Fuzzy Active Force Control and Skyhook Adaptive Neuro Active Force Control. The suspension system was modelled based on a two degree-of-freedom quarter car configuration. A number of road profiles were also modelled as the main disturbance elements to evaluate the system robustness and vehicle dynamic performance related to ride comfort. Simulation results both in time and frequency domains demonstrate the effectiveness of the proposed AFC-based schemes in countering the disturbances and other loading conditions. The schemes show evidence of at least 33.9% improvement in performance over the passive suspension. This is complemented by an experimental study on a developed full scale quarter car suspension test rig which shows a very good agreement with the simulation counterpart.
format Thesis
author Priyandoko, Gigih
author_facet Priyandoko, Gigih
author_sort Priyandoko, Gigih
title Intelligent active force control of a vehicle suspension system
title_short Intelligent active force control of a vehicle suspension system
title_full Intelligent active force control of a vehicle suspension system
title_fullStr Intelligent active force control of a vehicle suspension system
title_full_unstemmed Intelligent active force control of a vehicle suspension system
title_sort intelligent active force control of a vehicle suspension system
publishDate 2009
url http://eprints.utm.my/id/eprint/13618/1/GigihPriyandokoPFKM2009.pdf
http://eprints.utm.my/id/eprint/13618/
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score 13.15806