引用本文:陶洪峰,董晓齐,杨慧中.参考轨迹更新的点到点迭代学习控制算法优化及应用[J].控制理论与应用,2016,33(9):1207~1213.[点击复制]
TAO Hong-feng,DONG Xiao-qi,YANG Hui-zhong.Optimal algorithm and application for point to point iterative learning control via updating reference trajectory[J].Control Theory and Technology,2016,33(9):1207~1213.[点击复制]
参考轨迹更新的点到点迭代学习控制算法优化及应用
Optimal algorithm and application for point to point iterative learning control via updating reference trajectory
摘要点击 2553  全文点击 1760  投稿时间:2015-12-08  修订日期:2016-05-05
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2016.50970
  2016,33(9):1207-1213
中文关键词  参考轨迹更新  迭代学习控制  性能指标  拉格朗日乘子  点到点
英文关键词  updating reference trajectory  iterative learning control  performance index  Lagrange multiplier  point to point
基金项目  国家自然科学基金项目(61273070, 61203092)资助.
作者单位邮编
陶洪峰* 江南大学教育部轻工过程先进控制重点实验室 214122
董晓齐 江南大学教育部轻工过程先进控制重点实验室 江苏 无锡 214122 
杨慧中 江南大学教育部轻工过程先进控制重点实验室 江苏 无锡 214122 
中文摘要
      针对受非重复扰动作用的离散线性系统的输出跟踪控制问题, 提出一种基于参考轨迹更新的点到点迭代 学习控制算法. 首先通过构建性能指标函数对控制器进行范数优化, 并给出相应的收敛性条件, 使得系统输出能够 跟踪上更新后参考轨迹处的期望点. 其次, 当系统输出端受到某批次非重复扰动的影响时, 进一步通过引入拉格朗 日乘子算法构造多目标性能指标函数, 以优化鲁棒迭代学习控制器, 达到提高收敛速度和跟踪精度的目的. 最后将 该算法应用于电机驱动的单机械臂控制系统中, 仿真结果验证了算法的合理性和有效性.
英文摘要
      For the output tracking control problem of discrete linear system with non-repetitive disturbance, a point to point iterative learning control algorithm based on updating reference trajectory is proposed. Firstly, the iterative learning controller is optimized by constructing performance index with norm function, and the corresponding convergence conditions are given, then the system output can track with the desired points in updating reference trajectory. Furthermore, when the system output is affected by non-repetitive disturbance in some trials, a new multi-objective performance index function is constructed by Lagrange multiplier algorithm, and the robust iterative learning controller is optimized to improve the convergence speed and tracking accuracy. Finally, the simulation results of the motor driven single mechanical arm control system show the effectiveness and feasibility of the proposed algorithm.