CONTROLLING AN ACTIVE SUSPENSION SYSTEM FOR FOUR WHEELS CAR BY COMBINING LQR METHOD AND PARTICLE SWARM OPTIMIZATION

Abstract

Particle swarm optimization (PSO) is one of the algorithms based on the
concept of the intelligent swarm to find solutions to optimization problems. In
this paper, the authors design a controller for the active suspension system on
the 1/4 electric car model based on the LQR method combined with the particle
swarm optimization (PSO) to optimize the values of the weights number in the
controller. The simulation results in Matlab - Simulink software environment
show that the active suspension system using the LQR controller combined with
the PSO algorithm improves the comfort and safety of electric cars when
compared with LQR controller and the passive suspension system.