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PIVOŇKA, P.; DOKOUPIL, J.
Original Title
Sliding Window Recursive Neural Networks Learning Algorithm and its Application on the Identification in Adaptive PID
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
This article deals with the implementation of the adaptive PID controller based on the principle of forced separation imposed on the identification and system control. Original implementation of both Gauss-Newton (GN) and Levenberg-Marquardt (LM) algorithms operating in recursive learning mode over exponential-sliding finite data window for modelling of nonlinear dynamic systems is suggested. Their dynamics can be represented by a feed forward neural network. Synthesis of the PID controller is achieved using the Ziegler-Nichols method which utilizes the linearized ARX model of the neural network at the working point of the process. Benefits of the suggested algorithms are illustrated in the example simulations on the mathematical model.
English abstract
Keywords
Levenberg-Marquardt, Gauss-Newton, sliding-exponential window recursive algorithms, neural networks, NARX, adaptive PID controller
Key words in English
Authors
RIV year
2011
Released
15.09.2010
Location
Theodor-Korner-Allee 16 D-02763 Zittau
ISBN
978-3-9812655-4-5
Book
17th Zittau East-West Fuzzy Colloquium
Pages from
55
Pages to
62
Pages count
8
BibTex
@inproceedings{BUT34626, author="Petr {Pivoňka} and Jakub {Dokoupil}", title="Sliding Window Recursive Neural Networks Learning Algorithm and its Application on the Identification in Adaptive PID", booktitle="17th Zittau East-West Fuzzy Colloquium", year="2010", number="1", pages="55--62", address="Theodor-Korner-Allee 16 D-02763 Zittau", isbn="978-3-9812655-4-5" }