Research On Positioning And Tracking System Of Cable Winding Truck Based On SST-SCKF-AMPC

In the process of mine production,the traditional cable reeling method cannot guarantee the effective power supply for a long time,so our group has developed a new remote-controlled mining cable winding truck in cooperation with National Energy Group’s Halwusu Opencast Coal Mine,which is used to reel and drag the cables,improving the mining efficiency of opencast coal mines significantly.However,operation mode of artificial remote control is susceptible to environmental impacts and there are safety hazards in the production process,while the realization of the cable winding truck autonomously following the electric shovel movement can effectively improve the operational efficiency and production operation guarantee,and can promote the intelligent and automated development of coal industry technology and equipment.Therefore,this paper is aimed at achieving the goal of keeping power supply to the cable winding truck by following the movement of the shovel independently,and studies and explores the cable winding truck positioning and tracking system.Firstly,according to the operation conditions and environment of the cable winding truck,a variety of positioning schemes are compared and analyzed,and Ultra Wide Band(UWB)positioning technology is selected,and the propagation characteristics and methods of UWB positioning are studied.Secondly,we compare several filtering optimization methods commonly used in the localization process,and improve the square root volume Kalman(SCKF)algorithm by using the symmetrically time-varying fading factor to form the symmetrically strong tracking of square root volume Kalman(SST-SCKF).The algorithm is compared with several improved algorithms under different operating conditions and abnormal noise interference,and it is verified that the algorithm can effectively improve the positioning accuracy.Thirdly,the improved positioning optimization algorithm is combined with the proposed positioning scheme,an experimental platform is built and dynamic simulations are conducted to test the positioning scheme and verify the effectiveness of the positioning scheme in this paper.Finally,according to the characteristics and operation requirements of the cable winding truck to choose a suitable vehicle trajectory tracking control method and propose adaptive model prediction(AMPC),according to the curvature of the road to adjust the controller output speed and prediction time domain,setting constraints to ensure driving stability,in the cable winding truck trajectory tracking efficiency at the same time,but also to ensure operational safety,Through the simulation comparison of trajectory tracking model with Matlab to verify the superiority of AMPC trajectory tracking controller.This paper studies the solution for cable winding truck to achieve autonomous following of electric shovel movement,improved the positioning optimization algorithm,which can be applied to the positioning of the tracking system,and proposes an efficient cable winding truck trajectory tracking controller to improve the efficiency and production safety of mine electric shovels,which can promote the intelligent development of mine electrical equipment and promote intelligent technology development in coal mines.There are 38 figures,6 tables and 55 references in this paper.