Abstract
his paper presents a conditioning scheme for a
linear control system which is enhanced by a neural network
(NN) controller and subjected to a control signal amplitude
limit. The neural network controller improves the performance
of the linear ciintrol system by directly estimating an actuatormatched, un-modelled, nnn-linear disturbance, in closed-loop,
and cnm ensating for it. As disturbances are generally known tu
he bounled, the nominal NN-control element is modified to retain
the known hound of the disturbance as its maximum amplitude.
The linear control element is ronditianed hy an anti-windup (AW)
compensator which ensures performance close
linear control system which is enhanced by a neural network
(NN) controller and subjected to a control signal amplitude
limit. The neural network controller improves the performance
of the linear ciintrol system by directly estimating an actuatormatched, un-modelled, nnn-linear disturbance, in closed-loop,
and cnm ensating for it. As disturbances are generally known tu
he bounled, the nominal NN-control element is modified to retain
the known hound of the disturbance as its maximum amplitude.
The linear control element is ronditianed hy an anti-windup (AW)
compensator which ensures performance close
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2004 IEEE Conference on Cybernetics and Intelligent Systems Singapore, 1-3 December, 2004 |
| Pages | 751-756 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2004 |