Robust Optimal Control for the Vehicle Suspension System With Uncertainties - Bai, Rui; Wang, He-Bin (IEEE transactions on cybernetics, 2022)
The suspension system is an important unit that affects vehicle performance, including handling stability and riding comfort. In order to improve vehicle performances, a novel robust optimal control strategy for the active suspension system in vehicles is proposed. To handle the parameter uncertainties and external random disturbances, the proposed optimal control strategy is designed by using the combination of the linear quadratic regulator (LQR) optimal control and sliding-mode control. First, by using the nominal model of the active suspension system without the uncertain parameters and the external random disturbances, an optimal control performance index is given, and the initial optimal controller is designed by using the LQR control strategy. Then, to handle the parameter uncertainties and the external disturbances, a robust optimal integral sliding-mode control strategy based on the initial optimal controller is designed, which not only can achieve the optimal control objective but also has good robustness to the uncertain parameters and external disturbances. By using the Lyapunov stability theory, stability analysis of the proposed robust optimal integral sliding-mode control strategy is performed. Finally, the collaborative simulation platform based on the Carsim and MATLAB/Simulink is developed. The simulation results illustrate the advantage of the proposed robust optimal control strategy for the suspension system.