A Data-driven Optimal Iterative Learning Control with Data Loss Compensation

被引：0
|
作者：
Lv, Yunkai [1 ]
Chi, Ronghu [1 ]
Lin, Na [1 ]
机构：
[1] Qingdao Univ Sci & Technol, Sch Automat & Elect Engn, Qingdao 266042, Peoples R China
来源：
PROCEEDINGS OF 2018 IEEE 7TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS) | 2018年
基金：
美国国家科学基金会;
关键词：
Optimal ILC; Data loss compensation; Data-driven control; Non-linear discrete-time systems; SYSTEMS;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this work, a control scheme with compensation along the iteration axis is discussed for discrete time nonlinear systems with random data loss. The loss of output data from sensor to controller is considered, and the data missing is described through a variable satisfying the Bernoulli distribution. The lost output value is estimated by using the time-varying parameter and the output value of the last iteration to compensate the influence of data loss on the plant. A numerical simulation example verifies the validity of the algorithm.
引用
收藏
页码：180 / 183
页数：4
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