Fuzzy logic control of active suspension system equipped with a hydraulic actuator
More details
Hide details
Mechanical Engineering Department, College of Engineering, University of Baghdad
Online publication date: 2023-09-29
Publication date: 2023-09-29
International Journal of Applied Mechanics and Engineering 2023;28(3):13-27
In this paper, the Active Suspension System (ASS) of road vehicles was investigated. In addition to the conventional stiffness and damper, the proposed ASS includes a fuzzy controller, a hydraulic actuator, and an LVDT position sensor. Furthermore, this paper presents a nonlinear model describing the operation of the hydraulic actuator as a part of the suspension system. Additionally, the detailed steps of the fuzzy controller design for such a system are introduced. A MATLAB/Simulink model was constructed to study the proposed ASS at different profiles of road irregularities. The results have shown that the proposed ASS has superior performance compared to the conventional Passive Suspension System (PSS), where the body displacement can be minimized to about 70.1 % and the settling time is reduced to about 48.4 %. Also, the results have shown that the actuator force can reach 68 % of the body weight under the worst studied road conditions.
The author would like to thank all the staff of the Mechanical Engineering Department, College of Engineering, University of Baghdad, for their support and assistance.
Kumar S., Medhavi A. and Kumar R. (2021): Optimization of nonlinear passive suspension system to minimize road damage for heavy goods vehicle.– International Journal of Acoustics and Vibrations, vol.26, No.1, pp.56-63.
Tamburrano P., Plummer A.R., Distaso E., and Amirante R. (2018): A review of electro-hydraulic servovalve research and development.– International Journal of Fluid Power, pp.1-23.
Lee J., Oh K. and Yi K. (2020): A novel approach to design and control of an active suspension using linear pump control-based hydraulic system.– Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol.234. No.5, pp.1224-1248.
Hua C., Chen J., Li Y. and Li L. (2018): Adaptive prescribed performance control of half-car active suspension system with unknown dead-zone input.– Mechanical Systems and Signal Processing, vol.111, pp.135-148.
Ahmed M. and Svaricek F. (2014): Adaptive anti-windup approach for vehicle semi-active suspension.– In Proceedings of 2014 International Conference on Modelling, Identification and Control, pp.265-270.
Liu Y.J., Zeng Q., Tong, S., Chen C.P. and Liu L. (2019): Actuator failure compensation-based adaptive control of active suspension systems with prescribed performance.– IEEE Transactions on Industrial Electronics, vol.67, No.8, pp.7044-7053.
Han, S. Y., Dong, J. F., Zhou, J., and Chen, Y. H. (2022): Adaptive fuzzy PID control strategy for vehicle active suspension based on road evaluation.– Electronics, vol.11, No.6, pp.921.
Na J., Huang Y., Wu X., Su S.F. and Li G. (2019): Adaptive finite-time fuzzy control of nonlinear active suspension systems with input delay.– IEEE Transactions on Cybernetics, vol.50, No.6, pp.2639-2650.
Hung N.C., Nhung N.T.B., Vu L.T.Y., Khai V.Q., Son T.A. and Thanh T.Q. (2020): Apply a fuzzy algorithm to control an active suspension in a quarter car by Matlab’s Simulink.– In Applied Mechanics and Materials, vol.902, pp.23-32.
D’Amato F.J. and Viassolo D.E. (2000): Fuzzy control for active suspensions.– Mechatronics, vol.10, No.8, pp.897-920.
Xiang D., Yuan J.Z., and Xu W. (2012): Study on fuzzy PID algorithm for a new active front steering system.– Journal of Control Engineering and Technology, vol.2, No.1, pp.24-29.
Han S.Y., Dong J.F., Zhou J. and Chen Y.H. (2022): Adaptive fuzzy PID control strategy for vehicle active suspension based on road evaluation.– Electronics, vol.11, No.6, pp.921.
Mahmoodabadi M.J. and Nejadkourki N. (2022): Optimal fuzzy adaptive robust PID control for an active suspension system.– Australian Journal of Mechanical Engineering, vol.20, No.3, pp.681-691.
Zhang B., Zhao H. and Zhang X. (2023): Adaptive variable domain fuzzy PID control strategy based on road excitation for semi-active suspension using CDC shock absorber.– Journal of Vibration and Control, doi.org/10.1177/10775463231152287.
Papadimitrakis M. and Alexandridis A. (2022): Active vehicle suspension control using road preview model predictive control and radial basis function networks.– Applied Soft Computing, vol.120, pp.108646.
Lushnikov N. and Lushnikov P. (2017): Methods of assessment of accuracy of road surface roughness measurement with profilometer.– Transportation Research Procedia, vol.20, pp.425-429.
Qin Y., Wang Z., Xiang C., Hashemi E., Khajepour A. and Huang Y. (2019): Speed independent road classification strategy based on vehicle response: Theory and experimental validation.– Mechanical Systems and Signal Processing, vol.117, pp.653-666.
Dong J.F., Han S.Y., Zhou J., Chen Y.H. and Zhong X.F. (2020): FNT-based road profile classification in vehicle semi-active suspension system.– In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1392-1397.
Ding R., Wang R., Meng X., Liu W. and Chen L. (2021): Intelligent switching control of hybrid electromagnetic active suspension based on road identification.– Mech. Syst. Signal Process, vol.152, pp.107355.
Liu W., Wang R., Ding R., Meng X. and Yang L. (2020): On-line estimation of road profile in semi-active suspension based on unsprung mass acceleration.– Mechanical Systems and Signal Processing, vol.135, pp.106370.
Bessa W.M., Dutra M.S. and Kreuzer E. (2022): Adaptive fuzzy control of electrohydraulic servosystems.– arXiv, doi.org/10.48550/arXiv.2205.15639.
Robert J.J., Kumar P.S., Nair S.T., Moni D.S. and Swarneswar B. (2022): Fuzzy control of active suspension system based on quarter car model.– Materials Today: Proceedings, vol.66, pp.902-908.
Kurian P.C., Gopinath A., Shinoy K.S., Santhi P., Sundaramoorthy K., Sebastian B. and Mookiah T. (2017): Design of servo scheme and drive electronics for the integrated electrohydraulic actuation system of RLV-TD.– Journal of The Institution of Engineers (India): Series C, vol.98, pp.757-769.
Mandal H., Bera S.K., Saha S., Sadhu P.K. and Bera S.C. (2018): Study of a modified LVDT type displacement transducer with unlimited range.– IEEE Sensors Journal, vol.18, No.23, pp.9501-9514.
Mittal R. and Bhandari M. (2015, April): Design of robust PI controller for vehicle active suspension system with hydraulic actuator.– In 2015 International Conference on Communications and Signal Processing (ICCSP), pp.0914-0918.
Journals System - logo
Scroll to top