加权超前开环PD型迭代学习控制  

The Weighted Leading Open-loop PD-type Iterative Learning Control

作　　者：侯卓生[1] 阮小娥[2] 

机构地区：[1]西北第二民族学院电子与信息工程系,宁夏银川750021 [2]西安交通大学管理学院,陕西西安710049

出　　处：《厦门大学学报（自然科学版）》2003年第3期305-309,共5页Journal of Xiamen University：Natural Science

基　　金：国家自然科学基金(60274055);福建省重点科技项目(2001H020)资助

摘　　要：对具有滞后的线性大工业过程提出了加权超前开环PD 型的迭代学习控制算法,建立了基本的迭代学习控制结构,给出了迭代学习控制算法关于控制系统的ε 收敛性的定义和证明,提出了理想轨线的δ 可达性的概念.数字仿真表明,迭代学习控制能有效改善控制系统的动态品质,如缩短过渡时间,抑制超调等,表明了迭代学习控制算法的有效性.In this paper, the weighted leading openloop PDtype iterative learning control algorithm for linear largescale industrial processes with time delays is studied. The basic iterative learning control structure is established. The εconvergence of the algorithms with respect to the control systems is defined and proved. The δreachability of the desired trajectories is given. Digital simulations show that the iterative learning control algorithms can remarkably improve the transient response performance of the systems, such as shorten the settling time and decrease the overshoot while the setpoints changes are imposed on real industrial processes control systems etc. This indicates the effectiveness of the iterative learning control algorithms.

关 键 词：线性大工业过程 加权超前开环PD型迭代学习控制 控制结构 控制系统 δ-可达性 

分 类 号：TP273.22[自动化与计算机技术—检测技术与自动化装置]