The Development And Application Of Engineering Vehicles Cluster Motion Controller

Construction vehicle cluster movement longitudinal path tracking control driving is one of the important directions of the development of intelligent unmanned driving in today’s diversified cities.Aiming at the difficulty of traditional single engineering vehicles to solve the problems of construction road traffic congestion,bad road environment,and waste of human resources that have been deteriorating in recent years,a longitudinal path tracking control algorithm for vehicle cluster motion is proposed;Shortening the distance between vehicles and vehicles reduces the fluctuation between vehicle distances;therefore,the research on the control of "cluster motion" of construction vehicles is crucial.At present,the introduction and application of fuzzy models have greatly expanded the field of fuzzy control research.The fuzzy sampling control algorithm of intelligent fleet in this paper can effectively feedback the smooth and stable speed value to achieve the purpose of longitudinal and stable path tracking and driving of the fleet.The vehicle cluster motion control system has strong application in detection accuracy,control speed,wireless communication,and has broad application prospects in many fields,such as military and civil.This paper takes the "cluster motion" control of construction vehicles as the research object,and the research contents are as follows:First,the design of the engineering vehicle cluster motion path tracking control system.The fleet control is based on the concept of "pilot - following" and includes two aspects: the path tracking of the lead car based on visual navigation and the cluster motion path tracking of the following car based on laser ranging.Second,for the actual vehicle cluster movement longitudinal path tracking road information,a mathematical model for the engineering vehicle cluster movement path tracking is established.The mathematical model describes the input value of the leading vehicle speed to ensure the distance between the front and rear vehicles and the vehicle speed error And the vehicle acceleration error tends to zero,so as to ensure the stable longitudinal tracking of the fleet.Thirdly,research the cluster motion path tracking control algorithm under the fleet fuzzy sampling control mode.First of all,the established mathematical model is fuzzy,and the method of fuzzy sampling controller is used,and the design of the closed-loop control system with input delay is also considered;then,the linear inequality is used to prove the stability of the system;finally,the MATLAB/Simulink software platform is used The fuzzy sampling control algorithm is used to analyze the simulation results,and the simulation results are compared with the classic PID simulation results.It is concluded that the fuzzy sampling control algorithm is more stable for vehicle speed control and more stable for vehicle spacing control.Fourth,the verification and analysis of the semi-physical experiment results of system path tracking.By constructing a longitudinal path tracking experimental platform for intelligent car clusters,saving and recording experimental data,and using MATLAB software to process the data,the semi-physical simulation experiment results verify the fuzzy sampling control algorithm Feasibility and effectiveness.