基于视野状态分析的机器人路径跟踪智能预测控制

武星, 楼佩煌, 杨雷

武星, 楼佩煌, 杨雷. 基于视野状态分析的机器人路径跟踪智能预测控制[J]. 机器人, 2009, 31(4): 357-364.
引用本文: 武星, 楼佩煌, 杨雷. 基于视野状态分析的机器人路径跟踪智能预测控制[J]. 机器人, 2009, 31(4): 357-364.
WU Xing, LOU Pei-huang, YANG Lei. Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking[J]. ROBOT, 2009, 31(4): 357-364.
Citation: WU Xing, LOU Pei-huang, YANG Lei. Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking[J]. ROBOT, 2009, 31(4): 357-364.

基于视野状态分析的机器人路径跟踪智能预测控制

详细信息
    作者简介:

    武星(1982- ),男,博士生.研究领域:智能机器人,运动控制,嵌入式系统等.
    楼佩煌(1962- ),男,硕士,教授,博士生导师.研究领域:智能机器人,高精密数控,柔性制造系统等.
    杨雷(1969- ),男,学士,高级工程师.研究领域:工厂自动化,智能物流系统等.

  • 中图分类号: TP24

Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking

  • 摘要: 为视觉导航自动导引车(AGV)的路径跟踪提出一种基于视野状态分析的智能预测控制模型.以最优偏差状态转化策略取代二次型指标函数对预测控制目标的描述,避免了纯代数优化方法面临的参数选择难题.提出一种同步控制算法,用于完全消除理想纠偏状态的两种路径偏差并维持无偏差跟踪状态.对于其它状态,则采取假设—预测—调整的迭代算法,以实现状态转化的协调性.数值仿真和实验证明,在不同偏差状态和速度下,该算法都能产生可实现的速度差控制量,同步、快速和平稳地消除两种路径偏差,而且,该算法计算量小,可满足嵌入式控制系统实时处理的要求.
    Abstract: An intelligent predictive control model based on state analysis of visual field is presented for path tracking of the automated guided vehicle(AGV) with vision navigation.An optimal conversion strategy of error states is used to replace the quadratic cost function and to describe the objective of predictive control,so difficulties in parameter selection of pure algebra optimizing methods can be avoided.A synchronous control approach is proposed to completely eliminate two path errors of the ideal rectification state and to keep an error-free tracking state eventually.For other states,an iterative algorithm with assumption-prediction-adjustment is used to realize a harmonious state conversion.Numerical simulations and tests demonstrate that a realizable speed difference output can always be generated to eliminate two path errors synchronously, quickly and smoothly at different error states and velocities.Furthermore,with its low computational complexity,the proposed algorithm can satisfy the demand from realtime processing of embedded control systems.
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出版历程
  • 收稿日期:  2008-07-07

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