IMPROVED GENETIC ALGORITHM FOR ENHANCING THE COMFORTNESS OF A PASSENGER CAR

Abstract

This paper mainly focusing the significance of effective and most powerful optimization technique Real coded Genetic
Algorithm (RGA) for vehicle system over Binary coded Genetic Algorithm (BGA). Normal Fuzzy Logic Controller (FLC)
can act intelligently to improve the comfort of passengers inside a car. For multi input controllers, the choice of scaling
factors of the FLC requires more effort and knowledge where most of the FLC designers struggle. In this paper the FLC
scaling factors have been identified with two different but similar optimization techniques – BGA and RGA. For the
optimization, the RMS value of car Body Acceleration (BA) is taken as the Performance Index (PI). The simulation work
has done in MATLAB/SIMULINK environment by considering the dual bump as the road disturbance input. The
effectiveness of the RGA tuned FLC (RGAFLC) is proved in comparison with the BGA tuned FLC (BGAFLC) for the
passenger car.