| With the rapid development of science and technology such as computer,communication,artificial intelligence and modern sensing technology,the research field of intelligent vehicle will enter a vigorous development period.The trajectory tracking control of intelligent vehicle is basic technology to realize the autonomous driving and automatic tracking.With the development of automatic control technology,a lot of control theories and control methods have been widely used in trajectory tracking control of intelligent vehicle.However,in the case of different vehicle driving speed and different road adhesion coefficient,the trajectory tracking problems have a different requirement.The tire adhesion is often saturated,and the tire lateral force approaches the adhesion limit when the vehicle is steered under high-speed or low-adherent road conditions.At this time,the vehicle is easily to lose lateral stability due to the tire sideslip.For this purpose,aiming at the problem for trajectory tracking of the intelligent vehicle in the case of three conditions,which include dry road at low speed,dry road at high speed and wet road at normal speed.This thesis mainly focuses on lateral and longitudinal coordinated control for trajectory tracking of intelligent vehicle based on the CarSim and Matlab/Simulink simulation environment.The main work is as follows:1.Research on Vehicle-tire Model Based on DynamicsAiming at the characteristics of longitudinal,lateral and yaw dynamics of vehicle motion control,a vehicle dynamics model is established.The characteristics of vehicle tire are analyzed by the Pacejka’89 tire model,and then the lateral and longitudinal forces of the tires are calculated.The vehicle dynamics model is simplified for active steering control of intelligent vehicle trajectory tracking.2.Research on Intelligent Vehicle Lateral Tracking Control Based on Model Predictive Control(MPC)AlgorithmAiming at the problem of lateral position tracking accuracy during the steering process of intelligent vehicles,the predictive model is converted by vehicle dynamics model in this thesis,and uses the MPC algorithm to realize the front steering active steering control of the intelligent vehicle.Simultaneously considering the uncertainty of vehicle modeling,an adaptive RBF neural network is used to compensate the uncertain parts of the model,and a RBF-MPC lateral control system is designed.Finally,the input of the intelligent vehicle consists of the output of MPC and the compensated output of adaptive RBF neural network.The simulation test shows that the control system can track the double lane change better in the dry road-normal speed condition.3.Research on sliding mode control(SMC)of longitudinal speed based on vehicle inverse longitudinal dynamicsIn this thesis,the SMC and the inverse longitudinal dynamics of the vehicle are used to design the layered longitudinal speed controller.The longitudinal speed tracking is achieved by coordinated control the throttle opening and the master cylinder pressure of the intelligent vehicle.Meanwhile,the simulation environment is established to analyze the performance of the longitudinal control system under different road surface adhesion coefficient conditions.4.Research on lateral and longitudinal coordinated control for tracking of intelligent vehicleAiming at the good conditions of dry road at low speed,a kinematics model of the vehicle is established.The position deviation at the center of the rear axle of the vehicle is used as the state variable,the deviation of the front-wheel angle and the longitudinal speed are used as the control variables,and the lateral and longitudinal coordinated control system is designed based on the MPC algorithm.Aiming at the dry road at high speed and wet road at normal speed,the lateral and longitudinal coordinated control system is designed based on the combination of the MPC lateral controller and the SMC longitudinal controller.Considering the correlation and coupling characteristics between the lateral and longitudinal dynamics of the intelligent vehicle,the longitudinal speed is used as the state variable of the lateral control system to achieve coordinated control of the engine throttle opening,the brake master cylinder pressure and the front-wheel angle.The test shows that the desired trajectory can be tracked at the desired speed by coordinated control system.Meanwhile,the lateral stability is improved during the process of trajectory tracking of intelligent vehicle in the case of complex condition. |
