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CLC number: TP273
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
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Hybrid internal model control and proportional control of chaotic dynamical systems
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QI Dong-lian, YAO Liang-bin. Hybrid internal model control and proportional control of chaotic dynamical systems[J]. Journal of Zhejiang University Science A, 2004, 5(1): 62-67.
@article{title="Hybrid internal model control and proportional control of chaotic dynamical systems",
author="QI Dong-lian, YAO Liang-bin",
journal="Journal of Zhejiang University Science A",
volume="5",
number="1",
pages="62-67",
year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.0062"
}
%0 Journal Article
%T Hybrid internal model control and proportional control of chaotic dynamical systems
%A QI Dong-lian
%A YAO Liang-bin
%J Journal of Zhejiang University SCIENCE A
%V 5
%N 1
%P 62-67
%@ 1869-1951
%D 2004
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2004.0062
TY - JOUR
T1 - Hybrid internal model control and proportional control of chaotic dynamical systems
A1 - QI Dong-lian
A1 - YAO Liang-bin
J0 - Journal of Zhejiang University Science A
VL - 5
IS - 1
SP - 62
EP - 67
%@ 1869-1951
Y1 - 2004
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2004.0062
Abstract: A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid internal model control and proportional control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.
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