Title :
Intelligent control for brake systems
Author :
Lennon, William K. ; Passino, Kevin M.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
fDate :
3/1/1999 12:00:00 AM
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;
Journal_Title :
Control Systems Technology, IEEE Transactions on
