湖南大学学报（自然科学版）2024，Vol.51Issue(12)：19-29,11.DOI:10.16339/j.cnki.hdxbzkb.2024247
结合粒子滤波状态观测的滑模自适应主动悬架控制
Sliding Mode Adaptive Active Suspension Control Combined with Particle Filter State Observation
摘要
Abstract
When applying active suspension control,challenges such as parameter perturbation and the inability to directly acquire state variables in the algorithm may arise.Therefore,developing a robust control algorithm based on state observation is crucial.In this paper,a dynamic model of semi-vehicle roll suspension is established.A nonlinear filtering function coordinates the suspension deflection and the vertical acceleration of the vehicle body.It is then combined with a fuzzy sliding mode algorithm to achieve continuous sliding mode switching by utilizing fuzzy approximation,aiming to improve the chattering problem.On this basis,the stability of the control system under parameter perturbation is proven through the Lyapunov method,and a parameter adaptive law is designed.Additionally,for the state variables that cannot be directly measured in the algorithm,a particle filter state observer is designed to estimate their values in real-time.Finally,simulation analyses are conducted under typical working conditions,such as sinusoidal road excitation and random road excitation.The results demonstrate that the designed observer can provide real-time and accurate state information required by the control algorithm,and the fuzzy sliding mode controller with parameter adaptability exhibits good robustness and greatly improves vehicle posture and ride comfort.关键词
主动悬架/粒子滤波状态观测器/参数自适应/模糊滑模Key words
active suspension/particle filter state observer/parameter adaptive/fuzzy sliding mode分类
交通工程引用本文复制引用
吴晓建,邹亮,张铭浩,江会华,刘卫东,胡家琦..结合粒子滤波状态观测的滑模自适应主动悬架控制[J].湖南大学学报（自然科学版）,2024,51(12):19-29,11.基金项目
国家自然科学基金资助项目(52262054,52202466,52062036),National Natural Science Foundation of China(52262054,52202466,52062036) （52262054,52202466,52062036）
