Stable anti-lock braking system using output-feedback direct adaptive fuzzy neural control

In this paper, an output-feedback direct adaptive fuzzy neural controller for an anti-lock braking system (ABS) is developed. It is assumed that only the system output, the wheel slip ratio, is available for measurement. The main control strategy is to force the wheel slip ratio tracking variant optimal slip ratios, which may vary with the environment and assumed to be known during the vehicle-stopping period. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. To demonstrate the effectiveness of the proposed method, simulation results are illustrated.