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
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” and a “genetic model reference adaptive controller”, and investigate their effectiveness in reducing the effects of variations in the process due to temperature
Keywords :
adaptive control; automobiles; braking; fuzzy control; intelligent control; model reference adaptive control systems; automobiles; base-braking control; brake systems; braking torque commanded; fuzzy model reference learning controller; genetic model reference adaptive controller; intelligent control; temperature effects; Adaptive control; Automotive engineering; Control systems; Humidity control; Intelligent control; Logic; Programmable control; Temperature control; Torque control; Vehicle safety;
Conference_Titel :
Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-2722-5
DOI :
10.1109/ISIC.1995.525105
