International Journal of Vehicle Structures and Systems

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Optimized Fractional-Order Proportional Integral Derivative Controller for Active Vehicle Suspension System Performance Enhancement


Affiliations
1 Mataria, Helwan University, Cairo, Egypt
2 Helwan, Helwan University, Cairo, Egypt
 

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In this paper, an optimal Fractional Order Proportional Integral Derivative (FOPID) controller is applied in vehicle active suspension system to improve the ride comfort and vehicle stability without consideration of the actuator. The optimal values of the five gains of FOPID controller to minimize the objective function are tuned using a Multi-Objective Genetic Algorithm (MOGA). A half vehicle suspension system is modelled mathematically as 6 degrees-of-freedom mechanical system and then simulated using Matlab/Simulink software. The performance of the active suspension with FOPID controller is compared with passive suspension system under bump road excitation to show the efficiency of the proposed controller. The simulation results show that the active suspension system using the FOPID controller can offer a significant enhancement of ride comfort and vehicle stability.

Keywords

Half vehicle active suspension; Fractional order PID controller; Multi-objective genetic algorithm; Ride comfort
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  • A. Shojaei, H. Metered, S.Shojaei and S.O. Oyadiji. 2013. Theoretical and experimental investigation of magneto-rheological damper based semi-active suspension systems, Int. J. Vehicle Structures & Systems, 5(3-4), 109-120. http://dx.doi.org/10.4273/ijvss.5.3-4.06.

  • H. Metered. 2010. Modelling and Control of Magneto Rheological Dampers for Vehicle Suspension Systems, PhD Thesis, School of Mech., Aerospace and Civil Engg., The University of Manchester, Manchester, UK.

  • H. Metered. 2012. Application of nonparametric magneto rheological damper model in vehicle semi-active suspension system, SAE Int. J. Passeng. Cars: Mech. Syst., 5(1), 715-726. https://doi.org/10.4271/2012-01-0977.

  • H. Metered, A. Elsawaf, T. Vampola and Z. Sika. 2015. Vibration control of MR-damped vehicle suspension system using PID controller tuned by particle swarm optimization, SAE Int. J. Passeng. Cars - Mech. Syst. 8(2), 426-435. https://doi.org/10.4271/2015-01-0622.

  • D.A. Crolla and M.B.A. Abdel-hady. 1991. Active suspension control; performance comparisons using control laws applied to a full vehicle model, Vehicle System Dynamics, 20(2), 107-120. https://doi.org/10.1080/00423119108968982.

  • G. Priyandoko, M. Mailah and H. Jamaluddin. 2009. Vehicle active suspension system using skyhook adaptive neuro-active force control, Mech. Systems and Signal Proc., 23(3), 855-868. https://doi.org/10.1016/j.ymssp.2008.07.014

  • J. Wang, D.A. Wilson, W. Xu and D.A. Crolla. 2005. Active suspension control to improve vehicle ride and steady-state handling. Proc. 44th IEEE Conf. Decision and Control and European Control Conf., Seville, Spain.

  • A. Shehata, H. Metered, and W.A.H. Oraby. 2015. Vibration control of active vehicle suspension system using fuzzy logic controller, Vibration Engg. and Tech. of Machinery, 23, 389-399.

  • Y.M. Sam, J.H. Osman and M.R.A.A. Ghani. 2004. A class of proportional-integral sliding mode control with application to active suspension system, Systems & Control Letters, 51(3-4), 217-223. https://doi.org/10.1016/j.sysconle.2003.08.007.

  • K.A. Tahboub. 2005. Active nonlinear vehiclesuspension variable-gain control, Intelligent Control, Proc. IEEE Int. Symp. Mediterrean Conf. Control and Automation, Limassol, Cyprus.

  • M.S. Kumar and S. Vijayarangan. 2006. Design of LQR controller for active suspension system, Indian J. Engg., and Materials Sci., 13(3), 173-179.

  • H. Li, J. Yu, C. Hilton and H. Liu. 2013. Adaptive sliding-mode control for nonlinear active suspension vehicle systems using T-S fuzzy approach, IEEE Trans. Industrial Electronics, 60(8), 3328-3338. https://doi.org/10.1109/TIE.2012.2202354.

  • A.S. Emam. 2017. Active vibration control of automotive suspension system using fuzzy logic algorithm, Int. J. Vehicle Structures & Systems, 9(2), 77-82. http://dx.doi.org/10.4273/ijvss.9.2.03.

  • H. Metered, M. Kozek and Z. Šika. 2015. Vibration control of active vehicle suspension using fuzzy based sliding surface, Int. J. Fuzzy Systems and Advanced Applications, 2, 41-48.

  • A.S. Emam and A.M.A. Ghany. 2010. Enhancement of ride quality of a quarter cars by using h∞ design of a robust LMI output feedback controller, Ain Shams J. Mech. Engg., 2, 35-43.

  • R. Wang, H. Jing, H.R. Karimi and N. Chen. 2015. Robust fault-tolerant H∞ control of active suspension systems with finite-frequency constraint, Mech. Systems and Signal Proc., 62-63, 341-355. https://doi.org/10.1016/j.ymssp.2015.01.015.

  • A.S. Emam and A.M. Abdel Ghany. 2012. Enhancement of ride quality of quarter vehicle model by using mixed h2/h∞ with pole-placement, Engg., 4(2), 126-132. https://doi.org/10.4236/eng.2012.42016.

  • A.S. Emam. 2015. Fuzzy self-tuning of PID controller for active suspension system, Adv. in Powertrains and Automotive, 1(1), 34-41. https://doi.org/10.12691/apa-1-1-4.

  • H. Khodadadi and H. Ghadiri. Self-tuning PID controller design using fuzzy logic for half car active suspension system, Int. J. Dynam. Control, 6(1), 224-232.

  • H. Metered, W. Abbas and A.S. Emam. Optimized proportional integral derivative controller of vehicle active suspension system using genetic algorithm, SAE Tech. Paper 2018-01-1399. https://doi.org/10.4271/2018-01-1399.

  • A.A. Zamani, S. Tavakoli and S. Etedali. 2017. Fractional order PID control design for semi-active control of smart base - isolated structures: A multiobjective cuckoo search approach. ISA Trans., 67, 222-232. https://doi.org/10.1016/j.isatra.2017.01.012.

  • J. Zhang and Y. Zhang. 2008. Fractional-order PID control and optimization for vehicle active steering, Proc. 7th World Congress on Intelligent Control and Automation, Chongqing, China.

  • X. Dong, D. Zhao, B. Yang and C. Han. 2016. Fractional-order control of active suspension actuator based on parallel adaptive clonal selection algorithm, J. Mech. Sci. and Tech. 30(6), 2769-2781. https://doi.org/10.1007/s12206-016-0538-2

  • H.D. Taghirad and E. Esmailzadeh. 1998. Automobile passenger comfort assured through LQG/LQR active suspension, J. Vibration and Control, 4, 603-618. https://doi.org/10.1177/107754639800400504.

  • S. Gad, H. Metered, A. Bassuiny and A.M.A. Ghany. 2017. Multi-objective genetic algorithm fractional-order PID controller for semi-active magnetorheologically damped seat suspension, J. Vibration and Control, 23(8), 1248-1266. https://doi.org/10.1177/1077546315591620.

  • S. Das, S. Saha, S. Das and A. Gupta. 2011. On the selection of tuning methodology of FOPID controllers for the control of higher order processes, ISA Trans, 50(3), 376-388. https://doi.org/10.1016/j.isatra.2011.02.003.

  • J.L. Cohon. 1978. Multi-objective Programming and Planning, Academic Press, New York.

  • S.Y. Moon and W.H. Kwon. 1998. Genetic-based fuzzy control for half-car active suspension systems, Int. J. Systems Science, 29, 699-710. https://doi.org/10.1080/00207729808929564.


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PDF Views: 119




  • Optimized Fractional-Order Proportional Integral Derivative Controller for Active Vehicle Suspension System Performance Enhancement

Abstract Views: 313  |  PDF Views: 119

Authors

A. S. Emam
Mataria, Helwan University, Cairo, Egypt
H. Metered
Helwan, Helwan University, Cairo, Egypt
A. M. Abdel Ghany
Helwan, Helwan University, Cairo, Egypt

Abstract


In this paper, an optimal Fractional Order Proportional Integral Derivative (FOPID) controller is applied in vehicle active suspension system to improve the ride comfort and vehicle stability without consideration of the actuator. The optimal values of the five gains of FOPID controller to minimize the objective function are tuned using a Multi-Objective Genetic Algorithm (MOGA). A half vehicle suspension system is modelled mathematically as 6 degrees-of-freedom mechanical system and then simulated using Matlab/Simulink software. The performance of the active suspension with FOPID controller is compared with passive suspension system under bump road excitation to show the efficiency of the proposed controller. The simulation results show that the active suspension system using the FOPID controller can offer a significant enhancement of ride comfort and vehicle stability.

Keywords


Half vehicle active suspension; Fractional order PID controller; Multi-objective genetic algorithm; Ride comfort

References





DOI: https://doi.org/10.4273/ijvss.10.4.15