Main Article Content

Malar Mohan K


The increased concern on ride comfort and handling characteristics of an automobile have led to extensive research on automobile suspension systems. The authors of this article propose an adaptive air suspension system with LQR control strategy. The LQR controller is tuned by a combination of PSO and manual tuning. A dynamic model of the air suspension system used in passenger vehicles is designed and simulated for both passive and adaptive systems using MATLAB/Simulink. Air suspension is a non-linear system and thus the authors have derived a stiffness equation for the same with minimal assumptions. A comparative analysis is performed with the widely used PID controller to compare the efficiency of the proposed controller. The results are obtained for bumps, pot holes and ISO standard random road conditions. The settling time, peak displacement and tuning strategies are compared and analyzed. The results show that the adaptive system can achieve better vibration isolation compared to passive system. On comparing the analysis parameters, it is seen that the LQR controller has better potential to improve ride comfort by reducing the maximum displacement amplitude of the vehicle by 89.88% and provide better handling characteristics by reducing the settling time of the system by 85%.

Article Details


[1] Ab Talib M H and Darus I Z M, Self-tuning pid controller with mr damper and hydraulic actuator for suspension system., Computational Intelligence, Modelling and Simulation (CIMSim), 2013 pp - 119-124. IEEE.
[2] Agostinacchio M, Ciampa D and Olita S , The vibrations induced by surface irregularities in road pavements–a Matlab® approach, European Transport Research Review 6(3): 267-275.
[3] Bao W N, Chen L P, Zhang Y Q and Zhao Y S , Fuzzy adaptive sliding mode controller for an air spring active suspension., International Journal of Automotive Technology 13(7): 1057-1065.
[4] Curtain R, Iftime O and Zwart H , A comparison between LQR control for a long string of SISO systems and LQR control of the infinite spatially invariant version, Automatica 46(10): 1604-1615.
[5] Darus R and Sam Y M , Modeling and control active suspension system for a full car model, Signal Processing & Its Applications, 2009. CSPA 2009. 5th International Colloquium pp - 13-18. IEEE.
[6] Esmailzadeh E and Taghirad H D , Active vehicle suspensions with optimal state-feedback control., International Journal of Modelling and Simulation 18(3): 228-238.
[7] Hrovat D , Applications of optimal control to advanced automotive suspension design. , Journal of Dynamic Systems, Measurement, and Control 115(2B): 328-342.
[8] Huseinbegovic S and Tanovic O , Adjusting stiffness of air spring and damping of oil damper using fuzzy controller for vehicle seat vibration isolation, Control and Communications, 2009. SIBCON 2009. pp - 83-92. IEEE.
[9] Kennedy, J.; Eberhart, R. , Particle swarm optimization, IEEE International Conference on Neural Networks, Vol. 4, pp.1942,1948 Nov/Dec.
[10] Kothandaraman, R., Satyanarayana, L., & Ponnusamy, L., Grey fuzzy sliding mode controller for vehicle suspension system., Journal of Control Engineering and Applied Informatics, 17(3), 12-19.
[11] Lee S J , Development and analysis of an air spring model, International Journal of Automotive Technology 11(4): 471-479.
[12] Li M, Li Z, Shen X and Guo J , Study on PID Control for Semi-active Air Suspension for Riding Comfort, Intelligent Systems (GCIS), 2010 Second WRI Global Congress pp - 47-50. IEEE.
[13] Li S, Yang S and Guo W , Investigation on chaotic motion in hysteretic non-linear suspension system with multi-frequency excitations., Mechanics Research Communications 31(2): 229-236.
[14] Li X, He Y, Liu W and Wei Y , Research on the vertical stiffness of a rolling lobe air spring. , Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 230(4): 1172-1183.
[15] Pedro J O, Dangor M, Dahunsi O A and Ali M M , Particle swarm optimized intelligent control of nonlinear full-car electrohydraulic suspensions. , IFAC Proceedings Volumes 47(3): 1772-1777.
[16] Pratheepa B, Modeling and simulation of automobile suspension system. , Frontiers in Automobile and Mechanical Engineering (FAME), 2010 pp - 377-382.
[17] Rajagopal, K., & Ponnusamy, L. , Biogeography-based optimization of PID tuning parameters for the vibration control of active suspension system, Journal of Control Engineering and Applied Informatics, 16(1), 31-39.
[18] Rao L G and Narayanan S, Sky-hook control of nonlinear quarter car model traversing rough road matching performance of LQR control., Journal of Sound and Vibration 323(3-5): 515-529.
[19] Unger A, Schimmack F, Lohmann B and Schwarz R , Application of LQ-based semi-active suspension control in a vehicle. , Control Engineering Practice 21(12): 1841-1850.
[20] Wang G, Chen C and Yu S, Optimization and static output-feedback control for half-car active suspensions with constrained information., Journal of Sound and Vibration 378: 1-13.