| The rapid popularization of cars not only promotes the development of society and improves people’s living standard,but also brings a lot of environmental and traffic problems.As the future development direction of the automobile industry,intelligent vehicle is one of the effective means to solve the problem of traffic congestion.As one of the core technologies of motion control,the lateral control of intelligent vehicle mainly realizes the lateral tracking of target trajectory by controlling steering system.The research content of this paper will focus on the trajectory tracking control direction of intelligent vehicles.In the research process,the trajectory tracking control method based on the traditional optimal preview control theory is firstly studied.Placed in the transverse angular velocity is constant,under the hypothesis of driver based on the track ahead of a little information,and vehicle motion state is reached expected point error,and the expected type method obtained expected yawing angular velocity,finally obtaining the ideal steering wheel Angle,tracking the target trajectory need establish at models of single point according to the relationship.Then,the Carsim and Simulink simulation platforms were built to verify the effectiveness of the singlepoint preview algorithm under different driving conditions.The simulation results show that the algorithm is only suitable for low-speed road with high adhesion coefficient,and has no good adaptability and stability.In view of this,in order to improve the adaptability of the controller,the yaw velocity derived above was selected as the reference value in combination with the sliding mode theory to design the sliding mode controller.Aiming at the chattering problem of sliding mode controller,the switching function is optimized by using fuzzy theory,and the fuzzy sliding mode trajectory tracking controller is designed.Finally,the co-simulation platform of Carsim and Simulink is used to verify the designed controller.The simulation results show that the effectiveness of the fuzzy sliding mode controller is verified by comparing the effects of the controller with and without gain switching.The adaptability of the fuzzy sliding mode controller to the speed is verified by comparing the effects of the controller under different speeds.The adaptability of fuzzy controller to road and speed is verified by comparing the effects of controller under different road adhesion coefficient and different speed.The stability and adaptability of the controller are further verified by comparing the effects of different speeds under the condition of constant curvature. |
