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A variable-parameter-model-based feedforward compensation method for tracking control

delete2020-05-01
delete7
PRE
AI
张
张代林 (Dailin Zhang) *
Z
Zining Wang
M
Masayoshi Tomizuka
DOI:10.1109/JAS.2020.1003135delete
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摘要

摘要

En 中文
Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parameter-model-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.
Keyword:
Disturbance observer
feedforward compensation
iterative learning control
parameter identification
system model
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期刊

I
IEEE-CAA Journal of Automatica Sinica
IF:
19.2
论文数:
1.5K
被引数:
1.3W

机构

University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 25.2W
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