Adaptive Controller Design Of Active Suspension Considering Vehicle Uncertainty

As a part of the vehicle,the suspension system plays an important role in restraining the vibration and adjusting the attitude of the vehicle body.The active suspension system can adapt to more complex and changeable conditions and achieve the goals that other types of suspension are difficult to achieve in some engineering fields because of its remarkable effect in the above aspects.This thesis mainly focuses on several types of problems faced by vehicles in the field of practical engineering:First of all,considering that the tire force is difficult to measure and the dynamic travel of the suspension is limited when the vehicle is running,a quarter active suspension dynamic model is established.In order to take into account the relationship between vehicle ride comfort and suspension dynamic stroke,the concept of differential homeomorphism is introduced,and a state space equation containing both the vertical displacement of the body mass center and the suspension dynamic stroke is constructed,so that the active suspension system can improve the vehicle ride performance while ensuring that the suspension dynamic stroke does not exceed the limit.In view of the limited dynamic travel of the suspension and the nonlinear force of the tire,the obstacle Lyapunov function is used to constrain the vibration range of the suspension,and the neural network function is used to estimate the nonlinear force.The simulation shows that the control strategy designed above can effectively improve the ride comfort and operation stability of the vehicle under the premise of ensuring that the dynamic travel of the vehicle suspension is limited.Secondly,considering the particularity of the vehicle’s working conditions or load,there are changes in the mass and attitude of the vehicle body during driving,resulting in changes in the centroid position of the vehicle body.In order to avoid the adverse impact of this kind of situation on vehicle performance,a dynamic model of one-half active suspension is established,and the body mass and centroid displacement are regarded as nonlinear functions that change with time,and the state space equation of the system is constructed.For the spring part,the neural network function is used to approximate the unknown nonlinear function,and the adaptive control law is designed to estimate the body mass and centroid displacement;For the unsprung part,zero dynamics is used to prove the stability of the system.The simulation results show that the controller designed above can greatly reduce the impact of the change of body centroid position on vehicle performance,and improve the ride comfort and operation stability of the vehicle.Finally,consider the problem that suspension components fail due to service life or external interference,which leads to the reduction of suspension vibration suppression effect.Aiming at the spring damping fault,this thesis analyzes the influence of the deviation between the spring and damper coefficients of the suspension system and the standard values on the vehicle driving performance.In order to avoid the serious consequences of this kind of fault,an active suspension model of the whole vehicle is established.Taking a suspension fault at the front wheel of the vehicle as an example,the fault coefficients of the spring and damper of the suspension are estimated with adaptive algorithm,and the external interference of the system is eliminated,and the control strategy of the active suspension system is given.The simulation results show that the controller designed above not only avoids the adverse consequences caused by suspension failure,but also significantly improves the ride comfort of the vehicle,and improves the driving safety of the vehicle.