A novel adaptive fuzzy logic controller (AFC) based on an interval type-2 fuzzy controller is proposed for vehicle non-linear active suspension systems. The adaptive strategy elicited from the least-mean-squares optimal algorithm is adopted to self-tune lower bounds and upper bounds of interval type-2 fuzzy membership functions (IMF2s). The IMF2s are utilized in the AFC design to deal with not only non-linearity and uncertainty caused by irregular road inputs and immeasurable disturbance, but also the potential uncertainty of experts knowledge and experience. A case study based on a quarter-vehicle active suspension model has demonstrated that the proposed type-2 controller significantly outperforms conventional fuzzy controllers of an active suspension and a passive suspension.
HrovatD.Ride improvements with unsprung mass dynamic absorbers for active suspension vehicles. Research Report SR-87–120 Ford Motor Company, 1987.
2.
ThompsonA. G.DavisB. R.Optimal linear active suspensions with derivative constraints and output feedback control. Veh. System Dynamics, 1988, 17, 179–192.
3.
HrovatD.Survey of advanced suspension developments and related optimal control applications. Automatica, 1997, 33(10), 1781–1817.
4.
NagaiM.Recent researches on active suspensions for ground vehicles. JSME Int. J. Ser. C, 1993, 36(2), 161–170.
5.
ChenS. T.TzuuS. L.FanC. K.Design of fuzzy controlles for active suspension system. Mechatronics, 1995, 5(4), 365–383.
6.
YunQ. Z.ZhaoY. S.YangH. Z.A dynamic sliding-mode controller with fuzzy adaptive tuning for an active suspension system. Proc. IMechE Part D: J. Automobile Engineering, 2007, 221, 417–428.
7.
RaoM. V. C.PrahladV. A.A tunable fuzzy logic controller for vehicle active suspension system. Fuzzy Sets Systems, 1997, 85, 11–21.
8.
FernandoJ.ViassoloD. E.Fuzzy control for active suspensions. Mechatronics, 2000, 10, 897–920.
9.
HuangS. J.ChaoH. C.Fuzzy logic controller for a vehicle active suspension system. Proc. Instn Mech. Engrs Part D: J. Automobile Engineering, 2000, 214, 1–12.
10.
HuangS. J.LinW. C.Adaptive fuzzy controller with sliding surface for vehicle suspension control. IEEE Trans. Fuzzy Systems, 2003, 11, 550–559.
11.
LianR.-J.LinB.-F.SieW.-T.Self-organizing fuzzy control of active suspension systems. Int. J. Systems Sci., 2005, 36, 119–135.
12.
SakmanL. E.RahmiG.Fuzzy logic control of vehicle suspensions with dry friction nonlinearity. Sadhana, 2005, 30(5), 649–659.
13.
HagrasH.A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Systems, 2004, 12(4), 152–539.
14.
ZadehL. A.The concept of a linguistic variable and its application to approximate reasoning-1. Inf. Sci., 1975, 8, 199–249.
15.
MendelJ.Advances in type-2 fuzzy sets and systems. Inf. Sci., 2007, 117, 84–110.
16.
MendelJ.New results about the centroid of an interval type-2 fuzzy set, including the centroid of a fuzzy granule. Inf. Sci., 2007, 112, 360–377.
17.
HagrasH.Type-2 flcs: A new generation of fuzzy controllers. IEEE Comput. Intell. Mag., 2007, 2(1), 30–44.
18.
SepúlvedaR.CastilloO.MelinP.Rodríguez-DíazA.MontielO.Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic. Info. Sci., 2007, 177(10), 2023–2048.
19.
AstudilloL.CastilloO.AguilarL. T.Intelligent control for a perturbed autonomous wheeled mobile robot: A type-2 fuzzy logic approach. J. Nonlinear Stud., 2007, 14, 37–48.
20.
LiangO.KarnikN.MendelJ.Connection admission control in atm networks using survey-based type-2 fuzzy logic systems. IEEE Trans. System Man Cybernetics, 2000, 30, 319–339.
JulioR. A.AlbertoV.Calculating functions of interval type-2 fuzzy numbers for fault current analysis. IEEE Trans. Fuzzy Systems, 2007, 15(1), 31–40.
25.
CouplandS.JohnR. I.An investigation into alternative methods for the defuzzilication of an interval type-2 fuzzy set. In Proceedings of the 2006 IEEE Conference on Fuzzy systems (FUZZ-IEEE 2006), 2006, pp. 7196–7203 (IEEE, New York).
CaoJ.LiuH.LiP.BrownD. J.Study on active suspension control system based on an improved half-vehicle model. Int. J. Automn Computing, 2007, 4(3), 236–242.
28.
TaghiradH. D.EsmailzadehE.Automobile passenger comfort assured through LQG/LQR active suspension. J. Vibr. Control, 1998, 4, 603–618.
29.
MamdaniE. H.Applications of fuzzy algorithms for control of simple dynamic plants. Proc. IEE, 1974, 121(12), 1585–1588.
30.
WuD.MendelJ. M.Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Systems, 2002, 10, 622–639.
31.
WindowB.Stationary and nonstationary learning characteristics of the lms adaptive filter. Proc. IEEE, 1976, 64, 151–1162.
32.
SunJ.Study on control technique for vehicle active suspension system PhD Thesis, Harbin Engineering University, Harbin, PR China, 2003.
