Active Vibration Control of Passenger Seat with HFPIDCR Controlled Suspension Alternatives
Authors: Devdutt, M. L. Aggarwal
Abstract:
In this paper, passenger ride comfort issues are studied taking active quarter car model with three degrees of freedom. A hybrid fuzzy – PID controller with coupled rules (HFPIDCR) is designed for vibration control of passenger seat. Three different control strategies are considered. In first case, main suspension is controlled. In second case, passenger seat suspension is controlled. In third case, both main suspension and passenger seat suspensions are controlled. Passenger seat acceleration and displacement results are obtained using bump and sinusoidal type road disturbances. Finally, obtained simulation results of designed uncontrolled and controlled quarter car models are compared and discussed to select best control strategy for achieving high level of passenger ride comfort.
Keywords: Active suspension system, HFPIDCR controller, passenger ride comfort, quarter car model.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125481
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1297References:
[1] Savaresi, S.M. & Spelta, C. (2009). A single-sensor control strategy for semi-active suspensions. IEEE Trans. Control Syst. Technol., 17, 143–52.
[2] Hong, F. & Pang, C.K. (2012). Robust vibration control at critical resonant modes using indirect-driven self-sensing actuation. Mechatronic Systems. ISA Trans., 51, 834–40.
[3] Aghababa, M.P. (2013). A fractional-order controller for vibration suppression of uncertain structures. ISA Trans., 52, 881–7.
[4] Sie, W.T., Lian, R.J. & Lin, B.F. (2006). Enhancing grey prediction fuzzy controller for active suspension systems. Veh. Syst. Dyn., 44(5), 407–430.
[5] Fialho, I. & Balas, G. J. (2002). Road adaptive active suspension design using linear parameter-varying gain-scheduling. IEEE Trans. Contr. Syst. Technology, 10(1), 43 -54.
[6] Huang, S.J., Lin & W.C. (2003). A neural network sliding controller for active vehicle suspension. Materials Science Forum, 440-441, 119-126.
[7] Lauwerys, C., Swevers, J. & Sas, P. (2005). Robust linear control of an active suspension on a quarter car test-rig. Control Engineering Practice, 13(5), 577-586.
[8] Huang, S.J. & Chen, H.Y. (2006). Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control. Mechatronics, 16, 607–22.
[9] Mouleeswaran, S. (2008). Development of active suspension system for automobiles using PID controller. Proceedings of the World Congress on Engineering Vol. II WCE 2008, July 2 -4, 2008, London, U.K.
[10] Salem, M.M.M. & Aly, A.A. (2009). Fuzzy control of a quarter-car suspension system. World Academy of Science, Engineering and Technology, 3 (5), 224-229.
[11] Shirjoposht, N.P., Hassanzadeh, I., Hashemzadeh, F. & Alizadeh, G. (2010). Optimal active suspension control based on a quarter-car model: an analytical solution. International Journal of Vehicle Safety (IJVS), 5(1), 1-20.
[12] Sun, W., Gao, H. & Kaynak, O. (2011). Finite frequency H∞ control for vehicle active suspension systems. IEEE Trans. Control Syst. Technol, 19, 416–22.
[13] Ismail, M. F., Peng, K., Hamzah, N., Sam, Y.M., Aripin, M.K. & Hasan, M.H.C. (2012). A linear model of quarter car active suspension system using composite nonlinear feedback control. Proceeding of the IEEE Student Conference on Research and Development (SCOReD '12), Pinang, Malaysia, December 98–103
[14] Ansari, F.A. & Taparia, R.S. (2013). Modeling, analysis and control of active suspension system using sliding mode control and disturbance observer. International Journal of Scientific and Research Publications, 3(1), 1-6.
[15] Sun, W., Pan, H., Zhang, Y. & Gao, H. (2014). Multi-objective control for uncertain nonlinear active suspension systems. Mechatronics, 24(4), 318–327.
[16] Emam, A.S. (2015). Fuzzy Self Tuning of PID controller for active suspension system. Advances in Powertrains and Automotives, 1(1), 34-41.
[17] Shabani, H., Vahidi, B. & Ebrahimpour, M. (2013). A robust PID controller based on imperialist competitive algorithm for load–frequency control of power systems. ISA Transactions, 52, 88–95.
[18] Aboelela, M.A.S., Ahmed, M.F. & Dorrah, H.T. (2012). Design of aerospace control systems using fractional PID controller. Journal of Advanced Research, 3(3), 225–232.
[19] Vanavil, B., Chaitanya, K. K. & Rao, A.S. (2015). Improved PID controller design for unstable time delay processes based on direct synthesis method and maximum sensitivity. International Journal of Systems Science, 46(8), 1349–1366.
[20] Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(5), 338–353.
[21] Mamdani, E. & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1-13.
[22] Topalov, A. V., Yesim, O., Kayacan, E. & Kaynak, O. (2011). Neuro-fuzzy control of antilock braking system using sliding mode incremental learning algorithm. Neurocomputing , 74(11), 2011, 1883-1893.
[23] Boada, B. L., Boada, M. J. L. & Diaz, V. (2005). Fuzzy-logic applied to yaw moment control for vehicle stability. Vehicle System Dynamics, 43(10), 753-770.
[24] Lin, Y. J., Lu, Y. Q. & Padovan, J. (1993). Fuzzy logic control of vehicle suspension systems. International Journal of Vehicle Design, 14(5), 457-470.
[25] Çetin, S. & Akkaya, A.V. (2010). Simulation and hybrid fuzzy-PID control for positioning of a hydraulic system. Nonlinear Dynamics, 61(3), 465–476.
[26] Demir, O., Keskin, I., Cetin, S. (2012). Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach. Nonlinear Dynamics, 67(3), 2139–2151.
[27] Devdutt & Aggarwal, M.L. (2014) Fuzzy control of passenger ride performance using MR shock absorber suspension in quarter car model. International Journal of Dynamics and Control DOI 10.1007/s40435-014-0128-z.