Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Abstract

The hydro-pneumatic suspension, as a widely used suspension for heavy vehicles, has been taken seriously by researchers for a long time because it is crucial in terms of handling stability, riding comfort, and driving safety of these vehicles. Most previous studies only discussed the control of ride comfort or vehicle handling stability of the suspension system separately. This article proposes a dynamic switch control strategy which can switch between ride comfort and handling stability controllers under different road surfaces and driving conditions. The load transfer ratio (LTR) is selected as the switch performance index, and it is calculated through a six-degrees-of-freedom (6-DOF) model. The ride comfort and handling stability controller of the hydro-pneumatic suspension are designed based on the sliding mode control theory. The objective functions of parameters optimization of the sliding mode controller (SMC) are obtained by means of analytic hierarchy process (AHP), and then the controller’s parameters are optimized by the parallel adaptive clonal selection algorithm (PACSA). The simulation results based on MATLAB/Simulink show that: (1) the PACSA performs better than a genetic algorithm in terms of the parameters optimization of the SMC; (2) the proposed switch control strategy can simultaneously improve the ride comfort and handling stability under several typical steering maneuvers and various road profiles compared with the conventional SMC-controlled suspension.