On adaptive iterative learning control algorithm for discrete-time systems with parametric uncertainties subject to second-order internal model

The adaptive iterative learning control methods is used to control discrete-time systems with time-iteration-varying uncertainties. By exploiting second-order internal model, the time-iteration varying law of uncertainties are derived. A robust adaptive iterative learning control approach is present...

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Bibliographic Details
Published in:2015 10th International Conference on Computer Science & Education (ICCSE) pp. 512 - 517
Main Authors: Baobin Liu, Wei Zhou
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2015
Subjects:
Adaptive iterative learning control
Adaptive systems
Algorithm design and analysis
discrete-time system
Discrete-time systems
exogenous disturbance
second-order internal model
time-iteration-varying unknown parameter
Trajectory
Uncertainty
ISBN:9781479965984, 1479965987
Online Access:Get full text
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Summary:The adaptive iterative learning control methods is used to control discrete-time systems with time-iteration-varying uncertainties. By exploiting second-order internal model, the time-iteration varying law of uncertainties are derived. A robust adaptive iterative learning control approach is presented for discrete-time systems with exogenous disturbance. The tracking error of the designed adaptive iterative learning control law converges to zero asymptotically as iteration number approaches to infinity even if reference trajectories varying from iteration to iteration. Numerical example is given to validate the adaptive iterative learning control technique.
ISBN:9781479965984
1479965987
DOI:10.1109/ICCSE.2015.7250300