改进PSO纯跟踪模型的隧道装备轨迹跟踪研究OA

In order to reduce the trajectory error of tunnel equipment and improve its tracking accuracy,an improved particle swarm optimization(SA-PSO)pure pursuit model based on simulated annealing was proposed in this paper.Firstly,the kinematic model of the four-wheel steering equipment is established,and then the probabilistic jump characteristics of the simulated annealing(SA)algorithm are introduced into the particle swarm algorithm,so that the particles can accept the poor solution with a certain probability,so as to effectively improve the problem of precocious convergence of the particle swarm algorithm.Secondly,the SA-PSO algorithm is used to dynamically adjust the forward-looking distance of the tunnel equipment to obtain the optimal forward-looking distance.Finally,in order to verify the control accuracy of the improved particle swarm optimization pure tracking model,the simulation results are compared with PSO and SA algorithms in MATLAB,and the simulation results show that when the path is followed under different working conditions,the maximum lateral error obtained by the model after tracking is 0.013 m and 0.069 m,respectively,and the mean lateral error is reduced by 89.57%and 56.83%,respectively,which effectively improves the tracking accuracy of the tunnel equipment.