Intelligent control for brake systems

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.