Genetic fuzzy self-tuning PID controllers for antilock braking systems

Since the emergence of PID controllers, control system engineers are in pursuit of more and more sophisticated versions of these controllers to achieve better performance, particularly in situations where providing a control action to even a minimal degree of satisfaction is a problem. This work is an attempt to contribute in this field. Variations in the values of weight, the friction coefficient of the road, road inclination and other nonlinear dynamics may highly affect the performance of Antilock Braking Systems (ABS). A self-tuning scheme seems necessary to overcome these effects. The addition of automatic tuning tool can track changes in system operation and compensate for drift due to aging and parameter uncertainties. The paper develops a self-tuning PID control scheme with application to ABS via combinations of fuzzy and Genetic Algorithms (GAs). Results are reported and discussed. PID ! " # $ % & ' $ . # ) * + , . # & " / + # 0 / 1 . 2 0 / 2 3 + 4 0 # ABS . # $ 56 2 + ABS : +3 8 ) + ' +3 8 . & 9 : 9 + ; < " 0 + * = 5 / . 9 : + ; < " . # < ) + 9 2 > 2 % 0 , 2 # $ 8 . 2 + ' # # :2 , 2 PID # $ / ABS & # $ " * # 8 54 . # :' 9 #9 ? + 2 $ < ) (T-S # & 9 + . 5 " / (Optimality) ;& 2 A 9 . / 4 (Genetic Algorithms) . 2 # / 0 9 # $ < / ' 9 . # # :' + # = B C PID 2 # A / & "/ ; 0 / ) & D # + / : 0 # '$ + , # 0 ! !: ! . 9 2 # / 0 / ) " / + . + + A / +& $ / ' + 4 & / 0 5:5 + 5 ' / 3 #2 , / %:5 ) / 0 / .