Research On Trajectory Tracking Control Of Distributed Drive Intelligent Vehicle Based On Disturbance Observer

Distributed drive intelligent vehicle(DDIV)has great potential to improve the safety,comfort and convenience of vehicle driving.And it has become an important direction of vehicle development in the future.However,the control system is more vulnerable to external interference,resulting in the decline or even instability of vehicle trajectory tracking control performance.The vehicle will be affected by multi-source disturbances such as sensor measurement noise,signal delay,controller input disturbance and system unknown input.The interaction of various disturbances lead to the decline or even instability of vehicle trajectory tracking control performance.The control of vehicle system dynamics is actually a process of counteracting the influence of disturbance,which can be reduced to a typical anti-interference control problem of multi-source disturbance system.In this paper,the trajectory tracking control system of DDIV is designed based on the control method of disturbance observer,which eliminates the influence of multi-source disturbance on vehicle dynamics control.It provides a new theoretical basis and technical support for further improving the performance of vehicle trajectory tracking control.Firstly,the structural characteristics of DDIV and the complexity of trajectory tracking control system are considered.The vehicle dynamics model,electric drive wheel model,tire model and trajectory tracking model are established.The action processes of different types of disturbances are analyzed and summarized,and the control method based on disturbance observer is proposed to design the vehicle trajectory tracking control strategy.It lays a foundation for the research of trajectory tracking control of DDIV under the action of sensor measurement noise,signal delay and compound disturbance.Secondly,according to the advantage of information redundancy of distributed drive structure,a driving state estimation method of DDIV considering noise disturbance is proposed.It is composed of virtual longitudinal force sensor(VLFS)and adaptive attenuated Kalman filter algorithm(AAKF).The iterative algorithm of switching gain matrix is used in the sliding mode observer to suppress the influence of sensor noise on the accuracy of longitudinal force estimation.At the same time,the time-varying attenuation factor and noise covariance are adaptively adjusted to improve the accuracy of vehicle driving state estimation and the anti-noise ability of the system.Thirdly,in order to improve the performance of vehicle trajectory tracking control under the action of signal delay,a distributed driving intelligent vehicle trajectory tracking control strategy considering time-delay disturbance is designed.A delay disturbance observer composed of "current statistics" model and adaptive Kalman filter algorithm is designed.The real-time estimated position of lane target point is used as the input of vehicle trajectory tracking controller.Then,the expected front wheel steering angle is derived through the model predictive control algorithm,and the yaw moment distribution scheme is designed according to the expected yaw rate.Through the tire longitudinal force optimal distribution algorithm,the trajectory tracking accuracy and stability of DDIV distributed driven intelligent vehicle under the action of time-delay disturbance are maintained.Fourthly,according to the trajectory tracking control target under the action of compound disturbance,a coordinated control strategy of trajectory tracking and stability of DDIV based on disturbance observer is proposed.By characterizing the compound disturbance input and describing the control problem,a compound disturbance observer composed of sliding mode observer and time delay estimator is designed,and the estimation results are used as the input of vehicle coordinated control.At the same time,the vehicle trajectory tracking coordination controller is designed by using the sliding mode control algorithm,in order to ensure the trajectory tracking accuracy and the driving stability of the DDIV under the action of disturbance.Finally,the Hi L test and real vehicle test are carried out to verify the proposed driving state estimation method,the trajectory tracking control strategy considering delay disturbance and the vehicle trajectory tracking compound disturbance control strategy of DDIV.The vehicle state estimation method is realized in the real vehicle experimental platform.The effectiveness of the proposed vehicle state estimation method is verified by chassis dynamometer bench test and real vehicle road test.Through the combination of software and hardware,the trajectory tracking control system of DDIV is built,and the Hi L test system is used to verify the operation effect of the proposed vehicle trajectory tracking control method considering delay disturbance and compound disturbance in the actual controller.The research shows that the proposed adaptive attenuated kalman filter(AAKF)vehicle state estimation method can effectively improve the accuracy of vehicle state parameters such as centroid sideslip angle,which provides favorable conditions for vehicle trajectory tracking accuracy and stability under disturbance conditions.In addition,the proposed trajectory tracking control strategy of DDIV can still track the reference trajectory effectively under the action of compound disturbance.The peak relative error(PRE)of lateral deviation and heading angle deviation are 0.02173 m and 1.16 deg respectively,and the root mean square error(RMSE)are 0.02978 m and 0.5464 deg respectively.The accuracy and stability of vehicle trajectory tracking have been restored to the original level,which shows that the proposed method can effectively offset the influence of compound disturbance on trajectory tracking control performance and improve the ability of vehicle motion control system to offset external disturbance.The research work has certain significance for improving the dynamic control level of DDIV and enriching the research content of existing vehicle antidisturbance control.