Data-driven Adaptive Iterative Learning Predictive Control

被引：0
|
作者：
Lv, Yunkai [1 ]
Chi, Ronghu [1 ]
机构：
[1] Qingdao Univ Sci & Technol, Sch Automat & Elect Engn, Qingdao 266042, Peoples R China
来源：
2017 6TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS (DDCLS) | 2017年
关键词：
Predictive iterative learning control; Data-driven control; Nonlinear discrete-time systems; MODEL; DESIGN; ROBOT;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new data-driven predictive iterative learning control(ILC) is proposed for same category discrete nonlinear systems in this work. The controller design only depends on the input/output data of the system and does not need explicit mathematical model. More prediction information along the iteration axis is utilized in the learning control law to improve the control performance. The applicability of the proposed methods is proved by simulation experiments.
引用
收藏
页码：374 / 377
页数：4
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