Experimental Investigation on Genetic Algorithm optimized Proportional Integral Derivative Based Active Suspension System

In this work, Genetic Algorithm (GA) optimized Proportional Integral Derivative (PID) controller is employed. The PID gain values are optimally tuned based on the objective function formulated using the Integral Time Absolute Error (ITAE) criteria of various suspension measures like vehicle body displacement, suspension and tire deflections. The proposed GAPID controller is experimentally validated through the 3-DOF quarter-car test rig model. The fabricated model with passive suspension system (PASS) and active suspension system (ACSS) provided with an electrical actuator as base excitation is pictured. The schematic representation of the fabricated test set-up with and without ACSS is also illustrated. Further, simulation and experimental response of the fabricated model with and without ACSS are compared. It is identified that the proposed GAPID controller attenuates the sprung mass acceleration by about 41.64 % and 29.13 % compared with PASS for the theoretical as well as experimental cases respectively.