Cooperative Adaptive Cruise Control Technology Based On Event-triggered PID

With the development of intelligent driving,Cooperative Adaptive Cruise Control(CACC)has become a hot topic in recent years.The technique can form a small vehicle spacing when avoiding the amplification of the disturbance along the vehicle string,thus enabling the driver to gain a better driving experience.At the same time,CACC system can significantly increase road safety and traffic throughput,and can reduce energy consumption.Indeed,the traditional time-triggered control mode cycle is sampled and calculated,so it leads to many unnecessary operations of the controller,thereby resulting in a great waste of computer resources.For this problem,the event-triggered control method provides a good solution,which can effectively reduce the redundant calculation of the computer under the premise of ensuring the control performance of the system.Therefore,in order to reduce the redundant calculation of the control system and effectively improve the performance of the CACC system,the computational unit of the control algorithm can be limited to computing only if necessary.In order to achieve the goal,this paper proposes a control scheme based on event-triggered PID,which can effectively reduce the redundant calculation of the computer and ensure the closed-loop performance required by the system.The research contents are as follows:(1)An algorithm based on event-triggered PID control is proposed.First,the corresponding event-triggered conditions are designed according to the control system.Then,the PID controller based on event-triggered control is designed.The design flow of event-triggered algorithm is analyzed.Finally,the calculation part of the algorithm is optimized by using event-triggered control mechanism.The results show that the algorithm can effectively reduce redundant calculation,reduce the burden of controller and save computer resources.(2)An algorithm based on event-triggered neural network PID control is proposed to improve the control algorithm by introducing neural network in event-triggered PID control to make it have better control performance.First,this paper introduces the learning mode of neural network,then designs an event-triggered neural network PID controller,and analyzes the learning process of neural network PID control algorithm.Finally,a simulation experiment is designed according to the controller designed in this paper,and the experimental results are analyzed.The results show that the proposed algorithm can effectively solve the problem that PID controller parameters are not easy to set,and can reduce the number of PID operations and reduce the burden of the controller.(3)An event-triggered neural network PID algorithm based on feedforward-feedback control is proposed to compensate the external measurable disturbance by introducing feedforward control into the event-triggered neural network PID control,thus offsetting the effect of disturbance on the controlled object.In this paper,the influence of disturbance on the system is analyzed first,then the feedforward controller is designed according to the characteristics of the system,and the simulation experiments of the disturbance-free feedforward control and the disturbance-feedforward control are designed with the system control quantity and the system output parameters as the parameters to describe the system performance.