Lebesgue-p范数意义下区间可调节的变增益加速迭代学习控制  

Accelerated iterative learning control algorithm with variable gain and adjustment of interval in sense of Lebesgue-p norm

作　　者：兰天一[1] 林辉[1] 

机构地区：[1]西北工业大学自动化学院,西安710129

出　　处：《控制与决策》2017年第11期2071-2075,共5页Control and Decision

基　　金：国家自然科学基金项目(51407143);陕西省自然科学基础研究计划项目(2015JM5227)

摘　　要：为加快迭代学习控制律的收敛速度,针对线性时不变(LTI)系统,以PD-型学习律为例,提出一种区间可调节的具有指数加速的迭代学习控制算法.首先,根据每次学习效果确定下一次迭代需要修正的区间并在该区间内修正控制律增益;然后,在Lebesgue-p范数意义下分析所提出算法的收敛性并给出其收敛条件;最后,通过理论分析表明,收敛速度主要取决于被控对象、控制律增益、修正指数和学习区间的大小.在相同仿真条件下,与传统算法相比,所提出算法具有更快的收敛速度.In order to accelerate the convergence speed of iterative learning control（ILC） law, taking the PD-type learning law for example, an acceleration correction algorithm with variable gain and adjustment of learning interval is proposed for the linear time invariant（LTI） system. First of all, the modified interval in the next iteration is determined based on the learning effects, and the control law gain is modified in the interval. Then, analysis results show that the convergence speed mainly depends on the system state, the learning gain, the correction exponential and the learning interval in the sense of Lebesgue-p norm. In the same simulation condition, the proposed algorithm has a faster convergence speed compared with the traditional algorithms.

关 键 词：迭代学习控制 Lebesgue-p范数 收敛速度 增益调节 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]