| The rapid growth of vehicle population brings great convenience to the daily life of human beings and improve the efficiency of the society to a large extent.However,as a saying goes,every coin has two sides.It causes the increase of road safety accidents,serious traffic jams and the deterioration of energy and environmental problems.As a potential way to solve these problems,intelligent vehicles have attracted wide attention and are regarded as one of the revolutionary technologies that will change the world in the future.Recent years,thanks to the rapid development of technologies including sensor,computer,communication,and chip,the feasibility of autonomous driving is becoming more and more complete.However,in order to realize industrialization,there are still many technical problems to be solved.In this paper,the key and difficult problems in the practical application of motion control in intelligent vehicles are studied.Systematic solutions are provided to deal with the uncertain problems in the dynamics model as well as the coupling in the longitudinal and lateral motions.And an algorithm that integrates decision,planning and control is proposed to deal with the coordination between decision/planning and motion control.This paper lays the theoretical and technical foundation for the safe,stable and efficient driving of intelligent vehicles in various driving conditions and complex dynamic traffic environment.The main contents of this paper are given as follows:1)The nonlinear dynamics vehicle model with high DOF is built that contains the motions of vehicle body/wheels and the nonlinear tire model.Based on the established model,the coupling mechanism between the longitudinal and lateral motions of vehicle is analyzed in a systematical way.Then,the simplified vehicle dynamics model for controller design is established.By comparing with Carsim model in different working conditions,the feasibility of the simplified model is verified,and the influences caused by model uncertainties are analyzed.2)Aiming at the characteristics and respective problems of the longitudinal and lateral motions,the decoupling control algorithms are designed.In the lateral path following control,the uncertainties problems in some unconventional scenarios such as low adhesive condition are treated as the perturbation problem of cornering stiffness.A robust H? controller is established based on Linear Matrix Inequality.In order to ensure the transient performance of the controller,the poles of the closed-loop system are assigned.For the problem in longitudinal control that external disturbances such as wind are evident,a super-twisting sliding model controller is proposed based on high level sliding model theory.By utilizing this algorithm,the chattering near the sliding surface of the traditional sliding mode control method is well suppressed without weakening the anti-disturbance ability.3)For the conflict between path following control and dynamics stability in extreme driving conditions,a direct yaw moment controller(DYC)based on hierarchical structure is proposed that combines distributed driving technologies.For the upper level controller,a model predictive controller(MPC)based on kinematic relationships are proposed to get the desired yaw rate.The active yaw moment is calculated by the proposed hyperbolic tangent function based sliding mode controller.And the sliding surface is adaptive according to side slip phase plane to get a tradeoff between path following and dynamics stability under extreme conditions.And a logical variable is introduced to judge the involvement of active yaw moment in most normal conditions.Thus,unnecessary energy consuming is well prevented.In the tire force allocation,an optimization mechanism is proposed to make the most efficient utilization of tire adhesion.While the constraints on the general forces are flexible according to the driving condition.The flexible constraints on general forces can coordinate the longitudinal and lateral motion of vehicle in the tire force level without violating adhesive limits in extreme conditions.In this way,the safety of vehicle can be ensured.4)For the conservativeness problem of robust controller,a multi-model adaptive method is proposed.Firstly,the basic theory of the method is derived,and the adaptive law of each vertex sub-model to the real model is proposed,with its convergence proved by Lyapunov theory.Then,vehicle dynamics model and vehicle-road combined model are built,while the convex polyhedron including all possible perturbation of tire cornering stiffness is established by multi sub-models.The adaptive law is derived according to the vehicle dynamics model,while the feedback controller of sub-model in each vertex is derived by LQR method based on the vehicle-road combined model.Comparative study and Rapid Prototyping System experiment evaluate the effectiveness,advantages and enginnering application potential of the proposed algotirhm.5)Considering that for the classical heretical controller,the upper level controller and the tire force allocator will easily conflict with each other in extreme condition,a novel adaptive multiple-model predictive control(MPC)scheme for Four-Wheel Independent Drive(4WID)autonomous vehicles with a holistic structure is proposed.Firstly,the combined vehicle-path model is established.To ensure the real-time performance of MPC,the coupling relationships in the control output and the longitudinal/lateral motions are well decoupled,in this way a linear integrated model is utilized as the internal model of the controller,which can ensure the efficiency of the controller.Then,the holistic MPC is proposed to acquire the steering angle and the force on each corner.Based on the advantages of the proposed structure,a weight adaptive mechanism is introduced to improve the handling ability of the controller to various driving conditions,especially some extreme conditions.Moreover,by combing with the proposed multiple model adaptive law,the robustness of the controller is well ensured.6)In the research of autonomous vehicles,most existing studies treat the motion planning and tracking as two separate problems.This idea originates from robotics.But since there are essential differences between robot and autonomous vehicle.Considering planning and tracking separately may affect the performance of autonomous vehicle under complex driving conditions.To fill in the research gap and deal with the coordination problem between planning and control,this paper proposes a novel scheme which considers the local motion planning and control in a combined manner.Firstly,the local motion planning is transformed into the longitudinal control problem based on the proposed scenario adaptive MPC,by which the motion behavior can be automatically decided.Then,the lateral MPC controller is designed to track the global path and conduct the local motion commands.To ensure the performance of the path tracking and a smooth lane-change process simultaneously,an adaptive weight mechanism is introduced in the lateral controller. |
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