Adaptive fuzzy controller for vehicle active suspensions with particle swarm optimization

Abstract

With the particle swarm optimal (PSO) algorithm, an adaptive fuzzy logic controller (AFC) based on interval fuzzy membership functions is proposed for vehicle non-linear active suspension systems. The interval membership functions (IMFs) are utilized in the AFC design to deal with not only non-linearity and uncertainty caused from irregular road inputs and immeasurable disturbance, but also the potential uncertainty of expert's knowledge and experience. The adaptive strategy is designed to self-tune the active force between the lower bounds and upper bounds of interval fuzzy outputs. A case study based on a quarter active suspension model has demonstrated that the proposed adaptive fuzzy controller significantly outperforms conventional fuzzy controllers of an active suspension and a passive suspension.