Supervisory control of chaotic systems using online GA tuning neural networks

Yanqiu Che; Wang Jiang; Zhou Sisi

doi:10.1109/CHICC.2006.4347494

Supervisory control of chaotic systems using online GA tuning neural networks

Yanqiu Che, Wang Jiang, Zhou Sisi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present a controller for the supervisory backstepping control of a class of general nonlinear systems using online GA tuning neural networks (GNSB controller). The weights of the neural networks (NNs) approximator employed in the backstepping controller can successfully be turned via an online genetic algorithms (GAs) approach. The genetic algorithm has the capability of directed random search for global optimization. A simplified form of GA (SGA) approach is proposed to accelerate the search speed, and a new fitness function is established by the Lyapunov design method for the requirement of tuning the weights of the NNs online. A supervisory controller is used to guarantee the stability of the close-loop nonlinear system. Examples of Duffing chaotic system controlled by the presented controller are shown to illustrate the effectiveness of the proposed controller.

Original language	English (US)
Title of host publication	Proceedings of the 26th Chinese Control Conference, CCC 2007
Pages	193-197
Number of pages	5
DOIs	https://doi.org/10.1109/CHICC.2006.4347494
State	Published - Dec 1 2007
Event	26th Chinese Control Conference, CCC 2007 - Zhangjiajie, China Duration: Jul 26 2007 → Jul 31 2007

Other

Other	26th Chinese Control Conference, CCC 2007
Country/Territory	China
City	Zhangjiajie
Period	7/26/07 → 7/31/07

All Science Journal Classification (ASJC) codes

Computer Science Applications
Control and Systems Engineering
Applied Mathematics
Modeling and Simulation

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10.1109/CHICC.2006.4347494

Cite this

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title = "Supervisory control of chaotic systems using online GA tuning neural networks",

abstract = "In this paper, we present a controller for the supervisory backstepping control of a class of general nonlinear systems using online GA tuning neural networks (GNSB controller). The weights of the neural networks (NNs) approximator employed in the backstepping controller can successfully be turned via an online genetic algorithms (GAs) approach. The genetic algorithm has the capability of directed random search for global optimization. A simplified form of GA (SGA) approach is proposed to accelerate the search speed, and a new fitness function is established by the Lyapunov design method for the requirement of tuning the weights of the NNs online. A supervisory controller is used to guarantee the stability of the close-loop nonlinear system. Examples of Duffing chaotic system controlled by the presented controller are shown to illustrate the effectiveness of the proposed controller.",

author = "Yanqiu Che and Wang Jiang and Zhou Sisi",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/CHICC.2006.4347494",

language = "English (US)",

isbn = "7900719229",

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booktitle = "Proceedings of the 26th Chinese Control Conference, CCC 2007",

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T1 - Supervisory control of chaotic systems using online GA tuning neural networks

AU - Che, Yanqiu

AU - Jiang, Wang

AU - Sisi, Zhou

PY - 2007/12/1

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N2 - In this paper, we present a controller for the supervisory backstepping control of a class of general nonlinear systems using online GA tuning neural networks (GNSB controller). The weights of the neural networks (NNs) approximator employed in the backstepping controller can successfully be turned via an online genetic algorithms (GAs) approach. The genetic algorithm has the capability of directed random search for global optimization. A simplified form of GA (SGA) approach is proposed to accelerate the search speed, and a new fitness function is established by the Lyapunov design method for the requirement of tuning the weights of the NNs online. A supervisory controller is used to guarantee the stability of the close-loop nonlinear system. Examples of Duffing chaotic system controlled by the presented controller are shown to illustrate the effectiveness of the proposed controller.

AB - In this paper, we present a controller for the supervisory backstepping control of a class of general nonlinear systems using online GA tuning neural networks (GNSB controller). The weights of the neural networks (NNs) approximator employed in the backstepping controller can successfully be turned via an online genetic algorithms (GAs) approach. The genetic algorithm has the capability of directed random search for global optimization. A simplified form of GA (SGA) approach is proposed to accelerate the search speed, and a new fitness function is established by the Lyapunov design method for the requirement of tuning the weights of the NNs online. A supervisory controller is used to guarantee the stability of the close-loop nonlinear system. Examples of Duffing chaotic system controlled by the presented controller are shown to illustrate the effectiveness of the proposed controller.

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BT - Proceedings of the 26th Chinese Control Conference, CCC 2007

T2 - 26th Chinese Control Conference, CCC 2007

Y2 - 26 July 2007 through 31 July 2007

ER -

Supervisory control of chaotic systems using online GA tuning neural networks

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