On Finite-Iteration Convergence of Iterative Learning Control
- Resource Type
- Conference
- Authors
- Liu, Zhiqing; Chi, Ronghu; Liu, Yang
- Source
- 2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS) Data Driven Control and Learning Systems Conference (DDCLS), 2022 IEEE 11th. :670-675 Aug, 2022
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Learning systems
Control systems
Real-time systems
Data models
Linear matrix inequalities
Time-varying systems
Convergence
Iterative learning control
Finite-iteration convergence
2-D system theory
Linear time-varying systems
- Language
- ISSN
- 2767-9861
In this paper, a new problem of finite-iteration convergence of iterative learning control is discussed for a linear time-varying system. Considering a PD-type learning law, the finite-iteration convergence is shown by introducing two-dimensional system theory under some assumptions. By solving a set of linear matrix inequalities, the two learning gains of the control law can be updated in real time to ensure that the tracking error converges to an arbitrarily specified bound within finite iterative operations. Simulation study illustrates the correctness of the theoretical results.