This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front a...This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model.A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration.The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out,which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.展开更多
This paper reviews model predictive control(MPC)and its wide applications to both single and multiple autonomous ground vehicles(AGVs).On one hand,MPC is a well-established optimal control method,which uses the predic...This paper reviews model predictive control(MPC)and its wide applications to both single and multiple autonomous ground vehicles(AGVs).On one hand,MPC is a well-established optimal control method,which uses the predicted future information to optimize the control actions while explicitly considering constraints.On the other hand,AGVs are able to make forecasts and adapt their decisions in uncertain environments.Therefore,because of the nature of MPC and the requirements of AGVs,it is intuitive to apply MPC algorithms to AGVs.AGVs are interesting not only for considering them alone,which requires centralized control approaches,but also as groups of AGVs that interact and communicate with each other and have their own controller onboard.This calls for distributed control solutions.First,a short introduction into the basic theoretical background of centralized and distributed MPC is given.Then,it comprehensively reviews MPC applications for both single and multiple AGVs.Finally,the paper highlights existing issues and future research directions,which will promote the development of MPC schemes with high performance in AGVs.展开更多
基金supported by the National Natural Science Foundation of China(61573165,61520106008,61703178)
文摘This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model.A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration.The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out,which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.
基金This work was supported in part by National Natural Science Foundation of China(NSFC)under grant 61790564 and U1964202was supported in part by Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)under Germany’s Excellence Strategy-EXC 2075-390740016grant AL 316/11-2-244600449.
文摘This paper reviews model predictive control(MPC)and its wide applications to both single and multiple autonomous ground vehicles(AGVs).On one hand,MPC is a well-established optimal control method,which uses the predicted future information to optimize the control actions while explicitly considering constraints.On the other hand,AGVs are able to make forecasts and adapt their decisions in uncertain environments.Therefore,because of the nature of MPC and the requirements of AGVs,it is intuitive to apply MPC algorithms to AGVs.AGVs are interesting not only for considering them alone,which requires centralized control approaches,but also as groups of AGVs that interact and communicate with each other and have their own controller onboard.This calls for distributed control solutions.First,a short introduction into the basic theoretical background of centralized and distributed MPC is given.Then,it comprehensively reviews MPC applications for both single and multiple AGVs.Finally,the paper highlights existing issues and future research directions,which will promote the development of MPC schemes with high performance in AGVs.
