Performance and robustness assessment of H∞ active anti-roll bar control system by using a software environment

Abstract

Abstract The active anti-roll bar system has been proven to be one of the most effective solutions to improve roll stability of heavy vehicles. In a previous work, the authors proposed an H∞ controller for this system. The Genetic Algorithms method was used to handle the vehicle roll stability and the energy consumption of the actuators via the Pareto optimality. This paper aims to assess the overall effectiveness of the proposed controller with nonlinear heavy vehicle models, which are already set up in the TruckSim® software. The controller is then evaluated in hard conditions to show the high performance and robust with the nonlinearity effects, such as the load distribution between the two axles, the side wind gusts and the abrupt steering. To conduct testing of the H∞ active anti-roll bar control system, we propose a co-simulation structure between TruckSim® and Simulink®: the nonlinear vehicle model is determined from TruckSim®, based on using the block S-function of Simulink. Meanwhile, the controller and the actuators are built directly in the Matlab/Simulink ® environment. The validation results are made through two different types of heavy vehicles: a tour bus and a truck, using a selection of different velocities and scenarios. The results show that by using the H∞ active anti-roll bar control system, in comparison to the passive anti roll bar system, roll stability is improved to minimise the risk of vehicle rollover.