Nonlinear Optimal Control of Vehicle Active Suspension Considering Actuator Dynamics

Abstract

Considering the nonlinear characteristic of components in vehicle is very important in designing the controller of automobile active suspension system. To show the importance of this effect, a nonlinear optimal control method is employed in this paper. At first, an optimal law is developed for active suspension by the states prediction of a nonlinear quarter car model. The states of quarter car model are first predicted by Taylor series expansion and then a control law is introduced by minimizing the local differences between the predicted and desired states. In this way, the well defined sky hook linear model is selected as the reference model to be tracked by the nonlinear optimal controller. In order to decrease the vertical accelerations and improve the behavior of the reference model, the sky hook model is controlled beforehand by the LQR method. Derived control law has an analytical form which is easy to apply. The simulations show that under the proposed controller, the car has well passenger comfort and safe maneuverability.