Particle Swarm Optimization Technique for Rule Base Optimization of Flc for Low Speed Acc Vehicle

Adaptive Cruise Control is used in vehicles for giving support to the drivers and to circumvent rear end collision. Due to the presence of nonlinearity in the vehicle (system), it is difficult to design an exact mathematical model of the system. Heuristic based fuzzy logic controller with optimized rule base, which does not require accurate mathematical modelling is proposed here which uses the knowledge of the designer for developing the rule base. The performance metrics in terms of better control and response time of the controller depends upon how well the rule base is formulated. More the number of rules in the rule base, higher the search time and increase in the total response time of the system but better will be the control. On the other hand, if the rules are less, then the search time will reduce which in turn decreases the total time of response of the system but control will be poor. In order to obtain an optimized control, the rule base is optimized using Particle Swarm Optimization technique. The result had shown a better performance.