Using genetic programming to find Lyapunov functions

I.A.C. Soute; M.J.G. Molengraft, van de; G.Z. Angelis

Using genetic programming to find Lyapunov functions

I.A.C. Soute, M.J.G. Molengraft, van de, G.Z. Angelis

Control Systems Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to compute Lyapunov functions for. Although the OP algorithm is programmed to search for local stability, for most runs the result is a Lya punov function that assures global stability. Further testing is necessary to demonstrate if similar results can be obtained for more complex systems.

Original language	English
Title of host publication	Proceedings of theGenetic and evolutionary computation conference (GECCO2001), 7-11 July, 2001, San Francisco, California
Editors	C Ryan, L. Spector
Place of Publication	San Francisco
Publisher	Morgan Kaufmann Publishers, Inc.
Pages	449-452
ISBN (Print)	1-558-60774-9
Publication status	Published - 2001

Cite this

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title = "Using genetic programming to find Lyapunov functions",

abstract = "In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to compute Lyapunov functions for. Although the OP algorithm is programmed to search for local stability, for most runs the result is a Lya punov function that assures global stability. Further testing is necessary to demonstrate if similar results can be obtained for more complex systems.",

author = "I.A.C. Soute and {Molengraft, van de}, M.J.G. and G.Z. Angelis",

year = "2001",

language = "English",

isbn = "1-558-60774-9",

pages = "449--452",

editor = "C Ryan and L. Spector",

booktitle = "Proceedings of theGenetic and evolutionary computation conference (GECCO2001), 7-11 July, 2001, San Francisco, California",

publisher = "Morgan Kaufmann Publishers, Inc.",

address = "United States",

}

Using genetic programming to find Lyapunov functions. / Soute, I.A.C.; Molengraft, van de, M.J.G.; Angelis, G.Z.
Proceedings of theGenetic and evolutionary computation conference (GECCO2001), 7-11 July, 2001, San Francisco, California. ed. / C Ryan; L. Spector. San Francisco: Morgan Kaufmann Publishers, Inc., 2001. p. 449-452.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Using genetic programming to find Lyapunov functions

AU - Soute, I.A.C.

AU - Molengraft, van de, M.J.G.

AU - Angelis, G.Z.

PY - 2001

Y1 - 2001

N2 - In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to compute Lyapunov functions for. Although the OP algorithm is programmed to search for local stability, for most runs the result is a Lya punov function that assures global stability. Further testing is necessary to demonstrate if similar results can be obtained for more complex systems.

AB - In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to compute Lyapunov functions for. Although the OP algorithm is programmed to search for local stability, for most runs the result is a Lya punov function that assures global stability. Further testing is necessary to demonstrate if similar results can be obtained for more complex systems.

M3 - Conference contribution

SN - 1-558-60774-9

SP - 449

EP - 452

BT - Proceedings of theGenetic and evolutionary computation conference (GECCO2001), 7-11 July, 2001, San Francisco, California

A2 - Ryan, C

A2 - Spector, L.

PB - Morgan Kaufmann Publishers, Inc.

CY - San Francisco

ER -

Using genetic programming to find Lyapunov functions

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