Hybrid DEBBO algorithm for tuning the parameters of PID controller applied to vehicle active suspension system

This paper highlights the use of hybridizing biogeography-based optimization (bbo) with differential evolution (de) algorithm for parameter tuning of proportional integral derivative (pid) controller applied to vehicle active suspension system (vass). initially bbo,an escalating nature enthused global optimization procedure based on the study of the ecological distribution of biological organisms,and the hybridized debbo algorithm which inherits the behaviours of bbo and de,were used to find the tuning parameters of the pid controller to improve the performance of vass. simulations of passive system,active system,having pid controller with and without optimizations,were performed by considering trapezoidal,step and a random kind of road disturbances in matlab/simulink environment. the simulation results point out an improvement in the results with the debbo algorithm which converges faster than bbo. © 2015 jordan journal of mechanical and industrial engineering.