Abstract

The purpose of the sliding mode controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling asso- ciated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objec- tives, as possible. This paper deals with introducing a new technique such as Propor- tional Integral Sliding Mode controller(PISMC), sliding mode con- troller(SMC) and PID approaches to Half-Car Active Suspension to design a stability to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed con- troller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. Simulation results and a comparison with a calssical PID con- troller are presented and discussed. We studied the stabil- ity of the three used controllers in the presence of distur- bances. A good performance for the sliding mode controller (SMC) is achieved in simulation studies despite the disturbances.

References

• K. Sung, Y. Han, K. Lim and S. Choi. Discrete-time Fuzzy Sliding Mode Control for a Vehicle Suspension System Featuring an Electrorheological fluid damper. Smart Materials and Structures 16: pp. 798-808, 2007.
• M. Biglarbegian,W. Melek and F. Golnaraghi. A Novel Neurofuzzy Controller to Enhance the Performance of Vehicle Semiactive Suspension Systems, Vehicle System Dynamics, Vol. 46, No.8: pp. 691-711, 2008.
• M. Biglarbegian, W. Melek and F. Golnaraghi. Design of a Novel Fuzzy Controller to Enhance Stability of Vehicles, North American Fuzzy Information Processing Society: pp. 410-414, 2007.
• L. Yue, C. Tang and H. Li. Research on Vehicle Suspension System Based on Fuzzy Logic Control, International Conference on Automation and Logistics, Qingdao, China, 2008.
• M. Kumar. Genetic Algorithm-Based Proportional Derivative Controller for the Development of Active Suspension System, Information Technology and Control, Vol. 36, No. 1: pp.58- 67,2007.
• Ales Kruczek, Antonin Stribrsky, Jaroslav Honcu, Martin Hlinovsky.Controller choice for car active suspension. International Journal of Mechanics.V.3,2010.
• YM Sam,NM Suaib and Jhs Osman.Prportional integral sliding mode control for half car active suspension system with hydraulic actuator.conf.on Robotics,Control and Manufacturing Tchnology,2008.
• R.SPrabakar, C. Sujatha,S. Narayanan.Optimal semi-active preview control response of a half car vehicle model with magnetorheological damper.Journal of sound and vibration 326,pp 400-420,2009.
• Iraj Hassanzadeh, Gasem Alizadeh, Naser Pourqorban Shirjoposht, Farzad Hashemzadeh.A new optimal nonlinear approach to half car active suspension control.IACSIT International journal of engineering and technology.vol.2,No.1,2010.
• Jianfeng Wang and Chuanxue Song.Computer simulation on fuzzy control of semi active suspension system based on the whole vehicle.International journal of multimedia and ubiquitous engineering.Vol.8,No.6,2013.
• Ozgur Demir,Ilknur,Saban Cetin.Modeling and control of a nonlinear half-vehicle suspension system:a hybrid fuzzy logic approach.Nonlinear Dynamic,67,pp 2139-2151,2012.
• M. Jamei,M. Mahfouf,D.A. Linkens. Elicitation and finetuning of fuzzy control rules using symbiotic evolution.Fuzzy sets and system 147,pp 57-74,2004.
• Lemir Sakman,Rahmi Guclu and Nurkan yagiz.Fuzzy logic control of vehicle suspension with dry friction nonlinearity. Sadhana,v.30,pp 649-659’2005.
• Jiangtao Cao,Ping Li, Honghai Liu and David Brown.An interval type-2 fuzzy logic controller for quarter vehicle active suspensions.Journal of automobile engineering.
• Ayman A. Aly, A. Al Marakeby, Kamel A. Shoush.Active suspension control of a vehicle system using intelligent fuzzy technique.International journal of scientific and engineering research. V.4,2013.
• N. Ebrahimi, A.Gharaveisi.Optimal fuzzy supervisor controller for an active suspension system. International journal of soft computing and engineering,V.2,2012.
• A. Aldair and W. J. Wang.Adaptative neuro-fuzzy inference controller for full vehicle non linear active suspension.Iraq J. Electrical and electronic ingrneering.v.6,No .2,2010.
• M.A. Eltantawie.Decentralized neuro-fuzzy control for half car with semi active suspension system. International journal of automotive technology,vol.13,pp 423- 431,2012.
• Rajeswari Kothandaraman.PSO tuned adaptative neuro-fuzzy controller for vehicle suspension system.Journal of advances in information technology.vol.3,No.1,2012.
• Esmailzadeh, E. and Taghirad, H.D. Active Vehicle Suspensions with Optimal State-Feedback Control. Journal of Mechanical Science. 1996. 200(4): 1-18.
• Lu-Hang Zong,Xing-Long Gong,Chao-Yang Guo and Shou- Hu Xuan.Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system.Vehicle system dynamics.vol.50,No.7,pp 1025- 1041,2012.
• Alleyne, A. and Hedrick, J. K. Nonlinear Adaptive Control of Active Suspensions. IEEE Transactions on Control Systems Technology. 3(1): 94-101,1995.
• Fialho, I. and Balas, G.J. Road Adaptive Active Suspension DesignUsing Linear Parameter-Varying Gain- Scheduling. IEEE Transactions on Control Systems Technology. 10(1): 43-54,2002
• Yoshimura, T., Kume, A., Kurimoto, M., and Hino, J. Construction of An Active Suspension System of A Quarter Car Model Using The Concept of Sliding Mode Control. Journal of Sound and Vibration. 239(2): 187-199,2001
• Sam, Y.M. and Osman J.H.S. Modeling and Control of the Active Suspension using Proportional-Integral Sliding Mode Approach. Asian Journal of Control.2(7),pp:91-98.2005
• T.Takagi and M. Sugeno,derivation of fuzzy control rules from human operator s control actions.In:Proc.IFAC Symp. On fuzzy information, knowledge representation and decision analysis,pp:55-60, July 1983.