Fractional Order Networked Control System using Stochastic Iterative Learning Control
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Date
2022-12-30
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Citation of Original Publication
E. Shakeri and A. E. Abharian, "Fractional Order Networked Control System using Stochastic Iterative Learning Control," 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Maldives, Maldives, 2022, pp. 1-6, doi: 10.1109/ICECCME55909.2022.9987907.
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Subjects
Abstract
Networked control systems (NCSs) are one of the
main areas in control and computer engineering. Despite the
many advantages that NCSs have, they impose restrictions such
as random data dropout on control systems. We can remove the
impact of data dropout by employing the iterative learning
control (ILC) method for repetitive systems. In this paper, an
ILC for stochastic fractional order NCSs has been presented to
deal with the random data dropout imposed by the network.
Using the Kalman filter approach, the optimal learning gain is
determined so that the system output tracks to the desired
output in the presence of random data dropout. The simulation
results show that the mean of tracking error becomes close to
zero after 500 iterations when a significant number of data
packets have been lost in the network.