引用本文:周颖,何磊.具有控制时滞和测量数据丢失的直线电机迭代学习控制[J].控制与决策,2017,32(8):1434-1438
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具有控制时滞和测量数据丢失的直线电机迭代学习控制
周颖,何磊
(南京邮电大学自动化学院,南京210003)
摘要:
针对测量信号存在丢失和控制信号存在时滞的直线电机控制系统,研究PD型迭代学习控制算法的收敛性问题.假设数据丢失描述为概率未知的随机Bernoulli过程,其中丢失概率属于某个已知数值区间,利用超前法解决控制信号存在的时滞问题.基于Bellman-gronwall不等式和$\lambda$范数理论,证明了所提出的迭代学习控制策略能够使系统在有限时间内跟踪期望轨迹.最后通过仿真验证了所提出学习算法的有效性.
关键词:  控制时滞  测量数据丢失  直线电机  迭代学习
DOI:10.13195/j.kzyjc.2016.0738
分类号:TP273
基金项目:国家自然科学基金项目(61104103,61102155).
Iterative learning control for linear motor system with control delay and measurement dropout
ZHOU Ying,HE Lei
(College of Automation,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)
Abstract:
A PD-type iterative learning control(ILC) algorithm is proposed for the linear motor system in which there exist measurement signals dropout and control signals delay. The probability of the measurement dropout is unknown but belongs to a known numerical interval. The given advanced method is used to deal with the control delay. The convergence of the algorithm is proved by using Bellman-gronwall inequality and $\lambda$ norm theory. The simulation results demonstrate the effectiveness of the proposed algorithm.
Key words:  control delay  measurement dropout  linear motor  iterative learning

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