基于迭代学习理论的智能铲运机运动轨迹控制算法研究  

A Study on Control Algorithm for Kinematic Trajectory of Intelligent Scraper Built on Iterative Learning Theory

作　　者：姜勇[1] 

机构地区：[1]北京矿冶研究总院,北京100160

出　　处：《机械制造》2015年第11期4-7,共4页Machinery

基　　金：国家863高技术研究发展计划项目(编号:2011AA060403)

摘　　要：以智能铲运机为研究对象,建立了智能铲运机极坐标下的运动轨迹模型。针对地下智能铲运机的工作特性和控制技术要求,提出了一种基于迭代学习理论的开环和闭环迭代学习控制算法。该方法将每次迭代运行过程中的航向角偏差和轨迹偏差作为反馈修正量,不断地修正其在期望轨迹上的轨迹偏差,从而保证铲运机尽可能准确地跟踪期望轨迹,实现对其运动轨迹的精确控制。该方法在工程实践领域具有广阔的应用前景。It takes intelligent scrapers as the subject for investigation to establish a kinematic trajectory model under polar coordinates for the intelligent scrapers. Aiming at the characteristics of scrapers for underground operation and the requirements for intelligent control technology, an open-loop and closed-loop iterative learning control algorithm was set forth based on iterative learning theory. This method will take the course angle deviation and the trajectory deviation during each run of iteration as the feedback correcting data for continuous correction of the deviations in the desired trajectory, thereby the desired trajectory of the scraper could be tracked as accurately as possible in order to achieving accurate control of its kinematic trajectory. This method has broad application prospects in the field of engineering practice.

关 键 词：智能铲运机 运动轨迹 迭代学习 

分 类 号：TH123[机械工程—机械设计及理论] TP273[自动化与计算机技术—检测技术与自动化装置]