Nonlinear linearization controller and genetic algorithm-based fuzzy logiccontroller for ABS systems and their comparison

This paper addresses the design and performance of nonlinear controllers fo r Anti-lock Braking Systems (ABS). The controllers, based on a nonlinear fe edback linearization scheme and fuzzy logic control strategies, are designe d to solve the wheel slip-ratio tracking problem of a simplified quarter-ca r ABS model, respectively. Given the desired (optimal) wheel slip-ratio, th e feedback linearizing controller cancels all nonlinear dynamics and impose s an appropriate linear behaviour on the wheel slip-ratio such that it will track in a desired way. Using the slip-ratio error and the change-in-error measurements, fuzzy logic controllers have also been developed to resolve the wheel slip tracking problem. In contrast to conventional fuzzy logic co ntrol systems, a Genetic Algorithm (GA)-based fuzzy logic controller is pro posed to solve the same problem in which the explicit knowledge of paramete rs for the membership functions is deemed unnecessary. Numerical simulation s demonstrate the performance of the proposed control schemes subjected to different road conditions and in the presence of variations in system param eters and a bounded control input. The results indicate that superior perfo rmance can be obtained using the GA-based fuzzy logic controller when compa red with the feedback linearizing controller and the conventional fuzzy log ic controller.