The current path tracking control method is usually based on the steering wheel angle loop, which often makes the driver lose control of the automatic driving control loop. In order to involve the driver in the automatic driving control loop, and to solve the vehicle path tracking control problem with system robustness and model uncertainty, this paper puts forward a steering torque control method based on model predictive control algorithm. Based on the vehicle model, this method introduces the steering system model and the steering resistance torque model, and calculates the optimal control torque of the vehicle through the real-time vehicle status, so as to make up for the model mismatch, interference and other uncertainties, and ensure the real-time participation of the driver in the automatic driving control loop. To combine the nonlinear vehicle dynamics model with the steering column model, and to take the vehicle state parameters as the feedback variables of the model predictive controller model, then input the solution of the steering superposition control rate into the vehicle model, the design of the steering controller is realized. Finally, to carry out the simulation of lane keeping based on CarSim software and Simulink control model, and the hardware in-the-loop test on the hardware in-the-loop experimental platform of CarSim/LabVIEW-RT. The simulation and test results indicate that the designed torque loop path tracking control method based on model predictive control can help the driver track the target path better.
In terms of the research on electric power steering system, there are some problems, such as model uncertain and external interference. However, it is difficult for a general controller to deal with those problems as well as the performance of the system. Therefore, the paper is to propose a control method based on generalized internal model control, which is based on feedback and Youla parameterization, including performance controller and compensation controller. The performance controller is used to make the electric power steering system work well, while the compensation controller is used to solve model uncertain and external interference. First of all, the paper is to establish the model of electric power steering system, introduce the 2DOF vehicle and the tire model, set up the state space of the electric steering system including model uncertain and interference and design the generalized internal model controller. Finally, the simulation and the hardware-in-the-loop experiment are carried out to verify the controller. The results show that the proposed controller takes advantages of better control performance, solving model uncertain and external interference, and improving the performance and robustness of the system.
In view of the problem that the active suspension conflicts with the road tracking system while resisting roll when the commercial vehicle encounters emergency road conditions in the process of unmanned driving, this article is based on the Nash non-cooperative open-loop feedback game theory, taking the road tracking system, and the active anti-roll system as the participants of the game. An interactive control scheme which can not only accurately steer but also take into account the vertical roll stability is proposed. Firstly, the coupled model of Horizontal pendulum-anti-roll for commercial vehicles is established and extended to the vehicle-road three-degree of freedom closed model. Then, based on the derivation of the linear quadratic optimal control model (LQ), the non-cooperative open-loop Nash game theory is used to obtain the interactive optimal control afferent the road tracking system and the active anti-roll system. Finally, the experimental scheme is verified by hardware in the loop experiment. The results show that the interactive control scheme of road tracking and anti-roll based on Nash non-cooperative game for commercial vehicles allows the vehicle to take the vertical stability into account while turning actively, thus ensuring the safety and stability of the vehicle during driving.
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