基于改进型自适应超螺旋算法的主动悬架控制策略OA

To address the challenges of unmeasurable velocity signals and unknown bounds of lumped disturbances in active sus-pension systems,a control strategy based on an improved adaptive super-twisting algorithm is proposed.Firstly,considering the nonlinearity of the suspension system,parameter uncertainties,and external disturbances,a quarter-car active suspension dy-namic model is established with a balance between ride comfort and safety.Secondly,an improved adaptive super-twisting observ-er is designed to estimate the system states without requiring prior knowledge of the upper bound of the lumped disturbances,a-chieving finite-time convergence of observation errors.Then,by integrating dynamic surface control technology and using the backstepping method,an improved adaptive super-twisting controller is developed.It only requires the measurement of the sprung mass displacement to ensure finite-time convergence of the tracking error.Finally,the stability of the system is rigorously proved via Lyapunov analysis.Simulation results demonstrate that the proposed active suspension control strategy based on the improved adaptive super-twisting algorithm can effectively track the desired states while reducing chattering in the control output.