Nonlinear Repetitive Control for Mitigating Noise Amplification*

被引：2

作者：

Aarnoudse, Leontine ^{[1
]}

Pavlov, Alexey ^{[2
]}

Kon, Johan ^{[1
]}

Oomen, Tom ^{[1
,3
]}

机构：

[1] Eindhoven Univ Technol, Dept Mech Engn Control Syst Technol, Eindhoven, Netherlands

[2] NTNU Norwegian Univ Sci & Technol, Dept Geosci & Petr, Trondheim, Norway

[3] Delft Univ Technol, Delft Ctr Syst & Control, Delft, Netherlands

来源：

2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC | 2023年

关键词：

ITERATIVE LEARNING CONTROL; STEADY-STATE PERFORMANCE; DESIGN; SYSTEMS;

D O I：

10.1109/CDC49753.2023.10383495

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.

引用

页码：2891 / 2896

页数：6

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