Genetic optimization of a fuzzy active suspension system based on human sensitivity to the transmitted vibrations

Abstract

Optimization of a vehicle fuzzy active suspension (AS) controller was previously performed on the basis of the amplitude of transmitted vibrations to the body. However, ride comfort depends strongly on the human sensitivity, which is a function of not only the amplitude but also the frequency contents of the transmitted vibrations. In this paper, genetic optimization of a fuzzy AS system based on the human sensitivity to the transmitted vibrations is presented. For this purpose, a fuzzy logic controller (FLC) is initially proposed for the AS system control. The FLC parameters are then tuned using a genetic algorithm (GA). The tuning process is first formulated as a single-objective optimization problem based on the human sensitivity and conventional r.m.s. amplitude criteria separately. The simulation results reveal that the optimization of a fuzzy AS based on the common r.m.s. amplitude criterion not only does not result in the optimal ride index, but also causes a considerable increase in the energy consumption. Moreover, in order to accommodate the conflicting characteristics of the AS system, the FLC parameters are tuned on the basis of a multi-objective fitness function incorporating human sensitivity, suspension travel, and energy consumption. The simulation results prove the effectiveness of the optimized FLC in hitting the simultaneous targets of ride comfort improvement as well as suspension travel and energy consumption reduction.

Keywords

active suspension system human sensitivity fuzzy logic controller genetic optimization

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References

Reimpell

Stoll

The automotive chassis: engineering principles, 1996 (SAE International, Philadelphia, Pennsylvania).

Sharp

R. S.

Hassan

S. A.

The relative performance capabilities of passive active and semi-active car suspension systems. Proc. Instn Mech. Engrs, Part D: Transport Engineering, 1986, 200(D3), 219–228.

Thompson

A. G.

Pearce

C. E. M.

Physically realisable feedback controls for a fully active preview suspension applied to a half-car model. Veh. System Dynamics, 1998, 30(1), 17–35.

Nagai

Control and evaluation of active suspension for M.D.O.F. vehicle model. JSAE Rev., 1999, 20, 343–348.

Zhang

Alleyne

A practical and effective approach to active suspension control. Veh. System Dynamics, 2004, 43(5), 305–330.

Youn

Optimal preview control design of active and semi-active suspension systems including jerk. SAE technical paper 960936, 1996.

Yoshimura

Matumura

Kurimoto

Hino

Active suspension system of one-wheel car models using the sliding mode control with VSS observer. Int. J. Veh. Autonomous Systems, 2002, 1(1), 133–152.

8 ISO 2631-1. Mechanical vibrations and shock — evaluation of human exposure to whole-body vibration — part 1: general requirements, 1997 (International Standardization Organization, Geneva).

Zadeh

L. A.

Fuzzy sets. Inf. Control, 1965, 8(3), 338–353.

10.

D'Amato

F. J.

Viassolo

D. E.

Fuzzy control of active suspensions. Mechatronics, 2000, 10, 897–920.

11.

Abdelhady

M. B. A.

A fuzzy controller for automotive active suspension systems. SAE technical paper 2003-01-1417, 2003.

12.

Yoshimura

Watanabe

Active suspension of a full car model using fuzzy reasoning based on single input rule modules with dynamic absorbers. Int. J. Veh. Des., 2003, 31(1), 22–40.

13.

Holland

J. H.

Adaptation in natural and artificial system, 1975 (University of Michigan Press, Ann Arbor, Michigan).

14.

Cordona

Gomide

Herrera

Hoffmann

Magdalena

Ten years of genetic fuzzy systems: Current framework and new trends. Fuzzy Sets Systems, 2004, 141, 5–31.

15.

Kuo

Y. P.

T. H. S.

GA-based fuzzy PI/PD controller for automotive active suspension system. IEEE Trans. Ind. Electronics, 1999, 46(6), 1051–1056.

16.

Peng

Vadakkepat

Lee

T. H.

DNA code GA for the rule base optimization of a fuzzy logic controller. In Proceedings of the 2001 IEEE Conference on Evolutionary computation, Seoul, Republic of Korea, 27–30 May 2001, Vol. 2, pp. 1191–1196 (IEEE, New York).

17.

Jinzhi

Fan

Jun

An investigation of controller design for active suspension by using GA-based PID and fuzzy logic. SAE technical paper 2002-01-0983, 2002.

18.

Brandao

Howell

M. N.

Genetic learning and fuzzy controller applied to active suspension. SAE technical paper 2003-01-0133, 2003.

19.

Lin

J.-S.

Kanellakopoulos

Nonlinear design of active suspensions. IEEE Control Systems Maga., 1997, 17, 45–49.

20.

Els

P. S.

The applicability of ride comfort standards to off-road vehicles. J. Terramechanics, 2005, 42, 47–64.

21.

Linden

Test methods for ride comfort evaluation of truck seats. MSc Dissertation, Kungliga Tekniska Högskolan, Stockholm, Sweden, 2003.

22.

Shoenberger

R. W.

Human response to whole-body vibration. Perceptual Motor Skills, 1972, 34, 127–160.

23.

Jones

A. J.

Saunders

D. J.

Equal comfort contours for whole-body vertical pulses sinusoidal vibration. J. Sound Vibr., 1972, 23(1), 1–14.

24.

Miwa

Evaluation methods for vibration effect - part 2, measurement of equal sensation level for whole body between vertical and horizontal sinusoidal vibration. Int. Health (Japan), 1967, 5, 206–212.

25.

Kamal

M. M.

Wolf

J. A.

Jr.

Modern structural analysis, 1982 (Van Nostrand Reinhold, New York).

26.

Carstens

J. P.

Literature survey of passenger comfort limitation of high-speed ground transports. Report PB168, US Department of Commerce, Washington, DC, USA, 1965.

27.

Yang

Ren

Chen

Jiang

Yang

Study on ride comfort of tractor with tandem suspension based on multi-body system dynamics. Appl. Math. Modelling, 2007 (in press).

28.

Wong

J. Y.

Theory of ground vehicles, 2001 (John Wiley, New York).

29.

Montazeri-Gh

Jazayeri

Soleymani

Vehicle ride evaluation based on a time-domain variable speed driving pattern. Int. J. Veh. Des., 2008 (in press).

30.

Hrovat

Survey of advanced suspension developments and related optimal control applications. Automatica, 1997, 14, 471–496.