Comfort Improvement of an Adaptive Vehicle Suspension via Pointwise-Constrained Optimal Control

Abstract

This paper presents an adaptive optimal control strategy for an adaptive two-degree-of-freedom quarter car model with magnetorheological dampers. The method assumes the system is fitted with sensors to “read” the road profile ahead of the vehicle. The main objective of the adaptive optimal control is to minimise the root mean square acceleration of the sprung mass. Pointwise constraints (upper and lower suspension travel and minimum tyre vertical force) are considered instead of incorporating the constraints to the cost function via penalty methods. The implemented gradient optimisation routine, the so-called Method of Moving Asymptotes, shows very good performance for optimal controls subjected to large numbers of constraints. For the adaptive approach considered in this paper, the optimal intensity supplied to the MR damper remains constant unless either the quality of the road or the vehicle velocity change. The results obtained show that the adaptive optimal control obtains comfort improvements up to 63% with respect to the best passive constraint–abiding configuration.