Intelligent control for brake systems

Author

Lennon, William K. ; Passino, Kevin M.

Author_Institution

Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA

Volume

7

Issue

2

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

188

Lastpage

202

Abstract

There exist several problems in the control of brake systems including the development of control logic for antilock braking systems (ABS) and “base-braking.” Here, we study the base-braking control problem where we seek to develop a controller that can ensure that the braking torque commanded by the driver will be achieved. In particular, we develop a fuzzy model reference learning controller, a genetic model reference adaptive controller, and a general genetic adaptive controller, and investigate their ability to reduce the effects of variations in the process due to temperature. The results are compared to those found in previous research

Keywords

adaptive control; brakes; braking; fuzzy control; genetic algorithms; intelligent control; learning systems; model reference adaptive control systems; road vehicles; antilock braking systems; base-braking; braking torque; control logic; fuzzy model reference learning controller; general genetic adaptive controller; genetic model reference adaptive controller; Adaptive control; Automotive engineering; Control systems; Intelligent control; Logic; Programmable control; Stability; Temperature control; Torque control; Wheels;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/87.748145

Filename

748145