Research on Least Means Squares adaptive control for automotive active suspension

Author

Sun, Jianmin ; Yang, Qingmei

Author_Institution

Sch. of Mech.-Electron. & Automobile Eng., Beijing Univ. of Civil Eng. & Archit., Beijing

fYear

2008

fDate

21-24 April 2008

Firstpage

1

Lastpage

4

Abstract

According to the evaluation method of riding comfort and handling safety of automotive, the acceleration of the sprung mass, dynamic tyre load between wheels and road and dynamic deflection between the sprung mass and the unsprung mass are determined as the evaluation targets of suspension performance. The least means squares (LMS) adaptive algorithm is used in active suspension system. With adjusting the weight of adaptive filter, the minimum quadratic performance index is obtained. For two-DOF automotive suspension model, LMS adaptive control are studied. The simulation results show that LMS adaptive control is not only simple algorithm but also remarkably effective. The calculation of LMS adaptive control algorithm is much little, and the method is fit for the active control of the suspension system.

Keywords

adaptive control; automotive components; least mean squares methods; springs (mechanical); suspensions (mechanical components); automotive active suspension system; automotive handling safety; automotive riding comfort; dynamic tyre load; least means squares adaptive control; quadratic performance index; sprung mass acceleration; Acceleration; Adaptive algorithm; Adaptive control; Adaptive filters; Automotive engineering; Least squares approximation; Road safety; Tires; Vehicle dynamics; Wheels; Active control; Adaptive; Least Means Squares; control;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 2008. ICIT 2008. IEEE International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-1705-6

Electronic_ISBN

978-1-4244-1706-3

Type

conf

DOI

10.1109/ICIT.2008.4608474

Filename

4608474