Stochastic algorithm for PID tuning of bus suspension system

The objective of this paper is to improve the comfortness of the bus suspension system by means of suitable stochastic algorithms such as real coded genetic algorithm (RGA) and particle swarm optimization (PSO). In this paper, active suspension of a one-quarter-bus model is considered. The disturbance in the form of displacement is taken as input to the controller. The computation was originally explained and controlled using conventional PID controllers. RGA and PSO based controller are designed and applied to this bus suspension problem in order to minimize the oscillations thereby comfortness can be achieved. The response of the system using RGA and PSO based PID controller is compared with conventional algorithms. The results show that RGA based PID controller is superior in terms overshoot and settling time. The proposed controller is used such that the system is always operating in a closed loop, which will lead to better performance characteristics.