Simulation and experimental analysis of an active vehicle suspension system

This project was carried out to study the performance of a two degree-of-freedom (DOF) active vehicle suspension system with active force control (AFC) as the main proposed control technique. The overall control system essentially comprises two feedback control loops. First is intermediate AFC contr...

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Main Author:	Ahmad @ Manap, Mohd. Rizal
Format:	Thesis
Language:	English
Published:	2007
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/9541/1/MohdRizalAhmadMFKM2007.pdf
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id	my-utm-ep.9541
record_format	uketd_dc
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Ahmad @ Manap, Mohd. Rizal Simulation and experimental analysis of an active vehicle suspension system
description	This project was carried out to study the performance of a two degree-of-freedom (DOF) active vehicle suspension system with active force control (AFC) as the main proposed control technique. The overall control system essentially comprises two feedback control loops. First is intermediate AFC control loop for the compensation of the disturbances and second is the outermost Proportional-Integral-Derivative (PID) control loop for the computation of the optimum commanded force. Iterative learning method (ILM) and crude approximation (CA) were used as methods to approximate the estimated mass in the AFC loop. Both simulation and experimental studies were applied in this project. A quarter car model consists of sprung and unsprung masses is considered in developing of the computer simulation model in Simulink and also in the experimental set-up. Both simulation and experimental work were carried out and the results between the two of them are compared. The results of the simulation study show that active suspension system using AFC with CA and ILM gives better performance compared to PID controller and passive suspension system. Experimental results obtained in the study further verified the potential and superiority of the performance of the active suspension system with AFC strategy compared to the PID control.
format	Thesis
qualification_level	Master's degree
author	Ahmad @ Manap, Mohd. Rizal
author_facet	Ahmad @ Manap, Mohd. Rizal
author_sort	Ahmad @ Manap, Mohd. Rizal
title	Simulation and experimental analysis of an active vehicle suspension system
title_short	Simulation and experimental analysis of an active vehicle suspension system
title_full	Simulation and experimental analysis of an active vehicle suspension system
title_fullStr	Simulation and experimental analysis of an active vehicle suspension system
title_full_unstemmed	Simulation and experimental analysis of an active vehicle suspension system
title_sort	simulation and experimental analysis of an active vehicle suspension system
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2007
url	http://eprints.utm.my/id/eprint/9541/1/MohdRizalAhmadMFKM2007.pdf
_version_	1747814750408933376
spelling	my-utm-ep.95412018-10-14T07:19:56Z Simulation and experimental analysis of an active vehicle suspension system 2007-11 Ahmad @ Manap, Mohd. Rizal TJ Mechanical engineering and machinery This project was carried out to study the performance of a two degree-of-freedom (DOF) active vehicle suspension system with active force control (AFC) as the main proposed control technique. The overall control system essentially comprises two feedback control loops. First is intermediate AFC control loop for the compensation of the disturbances and second is the outermost Proportional-Integral-Derivative (PID) control loop for the computation of the optimum commanded force. Iterative learning method (ILM) and crude approximation (CA) were used as methods to approximate the estimated mass in the AFC loop. Both simulation and experimental studies were applied in this project. A quarter car model consists of sprung and unsprung masses is considered in developing of the computer simulation model in Simulink and also in the experimental set-up. Both simulation and experimental work were carried out and the results between the two of them are compared. The results of the simulation study show that active suspension system using AFC with CA and ILM gives better performance compared to PID controller and passive suspension system. Experimental results obtained in the study further verified the potential and superiority of the performance of the active suspension system with AFC strategy compared to the PID control. 2007-11 Thesis http://eprints.utm.my/id/eprint/9541/ http://eprints.utm.my/id/eprint/9541/1/MohdRizalAhmadMFKM2007.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:877?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering [1] P.G. Wright. (1984). The Application of Active Suspension to High Performance Road Vehicles, Microprocessors in Fluid Engineering IMechE Conference Publications. [2] http://www.lanciamontecarlo.net/Scorpion/Technical_Suspension.html [3] D. A. Crolla. (1988). Theoretical Comparisons of Various Active Suspension Systems in Terms of Performance and Power Requirements. in â€œAdvanced Suspensionsâ€?, Suffolk : Mechanical Engineering Publications Limited. pp 1 â€“ 9. [4] Alleyne, A., Neuhaus, P.D., Hedrick, J.K (1993). Application of Non Linear Control Theory to Electronically Controlled Suspension, Vehicle System Dynamics Vol. 22, No. 5-6, P.309-320. [5] Gopalasamy, S,. et. al.. (1997). Model Predictive Control For Active Suspension. Controller Design and Experimentally Study. Trans. of ASME, Journal of Dynamic Systems and Control, Vol. 61, pp. 725-733. [6] Hewit, J.R., (1998). Advances in Teleoperations, Lecture note on Control Aspects, CISM. [7] Mailah, M. and Yong, M.O., (2001). Intelligent Adaptive Active Force Control of a Robot Arm With Embedded Iterative Learning Algorithms, Jurnal Teknologi, UTM, No.35(A), pp. 85-98. [8] Musa Mailah. (1999). A Simulation Study on the Intelligent Active Force Control of A Robot Arm Using Neural Network, Jurnal Teknologi (D), Universiti Teknologi Malaysia. pp 55 â€“ 78. [9] Arimoto, S., Kawamura, S., and Miyazaki, F. (1986). Convergence, Stability and Robustness of Learning Control Schemes for Robot Manipulators, Recent Trends in Robotics: Modelling, Control and Education, ed. by Jamshidi M., Luh L.Y.S., and Shahinpoor M. 307 â€“ 316. [10] Zhang, Y. (2003). A hybrid adaptive and robust control methodology with application to active vibration isolation, University of Illinois, Urbana- Champaign, Ph.D. Thesis. [11] Baillie, A.S. (1999). Development of a fuzzy logic controller for an active suspension of an off-road vehicle fitted with terrain preview, Royal Military Collage of Canada, Kingstone, Canada, Ph.D. Thesis. [12] Dâ€™Amato, F. J. and Viassolo, D. E. (2000). Fuzzy Control for Active Suspensions, Mechatronics, 10: 897-920. [13] Omar, Z. (2002). Modelling and Simulation of an Active Suspension System Using Active Force Control Strategy, MSc. Project Report, Universiti Teknologi Malaysia. [14] Mailah M., Priyandoko G. (2005). Simulation of a Suspension System with Adaptive Fuzzy Active Force Control, International Journal of Simulation Modelling, Vol.6 No.1, pp 25-36. [15] G. Priyandoko, et al. (2007). Skyhook Adaptive Neuro Active Force Control for an Active Suspension System, Procs. Of CIM07, Johor Persada Convention Centre.

Simulation and experimental analysis of an active vehicle suspension system

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