Detail publikace

Adaptive Controller with Identification Based on Neural Network for Systems with Rapid Sampling Rates

VELEBA, V. PIVOŇKA, P.

Originální název

Adaptive Controller with Identification Based on Neural Network for Systems with Rapid Sampling Rates

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

In this paper ability of three identification methods to parameter estimation of the dynamic plant with great ratio of its time constant to sampling periods is compared. We concentrate our attention on dealing with adverse effects that work on real-time identification of process, especially quantization. It is shown, that a neural network applied to on-line identification process produces more stable solution in the rapid sampling domain. Taking advantage of this result, we propose here an adaptive controller with a neural network as on-line estimator. Simple heuristic synthesis based on modified Ziegler-Nichols open loop method (Z-N 1) are discussed, that deals with bad-estimated model of a plant and gives numerically stable parameters of the PID discrete controller.

Klíčová slova v angličtině

Rapid Sampling, Quantization, Neural Network, Training Set, Levenberg-Marquardt Minimization, Discrete PID Controller, RLS Identification Method

Autoři

VELEBA, V.; PIVOŇKA, P.

Rok RIV

2005

Vydáno

16. 6. 2005

ISSN

1109-2777

Periodikum

WSEAS Transactions on Systems

Ročník

4

Číslo

4

Stát

Spojené státy americké

Strany od

385

Strany do

388

Strany počet

4

BibTex

@article{BUT46303,
  author="Václav {Veleba} and Petr {Pivoňka}",
  title="Adaptive Controller with Identification Based on Neural Network for Systems with Rapid Sampling Rates",
  journal="WSEAS Transactions on Systems",
  year="2005",
  volume="4",
  number="4",
  pages="4",
  issn="1109-2777"
}