Identification and control of resonant switch mode converters using neural networks

M.N. Eskander, B. Baha

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

Abstract

Neural network (NNs) approach for controlling switching power converters has been investigated in this paper. Several NNs techniques including the Back propagation training algorithm, Back propagation with momentum, Back propagation with adaptive learning rate and the Back propagation with Levenberg Marquardt optimisation have been investigated and the most later method has been selected for identification and control of Quasi-Resonant Converters (QRCs). A neural network emulator is designed in this paper, which reproduce the converter dynamic behaviour with great accuracy. The NN controller is developed and applied to regulate the converter output voltage. Results obtained from the NNC proved the validity and fast dynamic response of the proposed controller.
Original languageEnglish
Title of host publicationProceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE
Pages2099-2104
Number of pages6
ISBN (Print)0780371089
Publication statusPublished - 2001
EventProceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society - Denver, CO, 29 Nov - 2 Dec, 2001
Duration: 1 Jan 2001 → …

Conference

ConferenceProceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society
Period1/01/01 → …

Fingerprint

Backpropagation
Switches
Neural networks
Controllers
Power converters
Dynamic response
Momentum
Electric potential

Cite this

Eskander, M. N., & Baha, B. (2001). Identification and control of resonant switch mode converters using neural networks. In Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society (pp. 2099-2104). IEEE.
Eskander, M.N. ; Baha, B. / Identification and control of resonant switch mode converters using neural networks. Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2001. pp. 2099-2104
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title = "Identification and control of resonant switch mode converters using neural networks",
abstract = "Neural network (NNs) approach for controlling switching power converters has been investigated in this paper. Several NNs techniques including the Back propagation training algorithm, Back propagation with momentum, Back propagation with adaptive learning rate and the Back propagation with Levenberg Marquardt optimisation have been investigated and the most later method has been selected for identification and control of Quasi-Resonant Converters (QRCs). A neural network emulator is designed in this paper, which reproduce the converter dynamic behaviour with great accuracy. The NN controller is developed and applied to regulate the converter output voltage. Results obtained from the NNC proved the validity and fast dynamic response of the proposed controller.",
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Eskander, MN & Baha, B 2001, Identification and control of resonant switch mode converters using neural networks. in Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society. IEEE, pp. 2099-2104, Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society, 1/01/01.

Identification and control of resonant switch mode converters using neural networks. / Eskander, M.N.; Baha, B.

Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2001. p. 2099-2104.

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

TY - GEN

T1 - Identification and control of resonant switch mode converters using neural networks

AU - Eskander, M.N.

AU - Baha, B.

PY - 2001

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N2 - Neural network (NNs) approach for controlling switching power converters has been investigated in this paper. Several NNs techniques including the Back propagation training algorithm, Back propagation with momentum, Back propagation with adaptive learning rate and the Back propagation with Levenberg Marquardt optimisation have been investigated and the most later method has been selected for identification and control of Quasi-Resonant Converters (QRCs). A neural network emulator is designed in this paper, which reproduce the converter dynamic behaviour with great accuracy. The NN controller is developed and applied to regulate the converter output voltage. Results obtained from the NNC proved the validity and fast dynamic response of the proposed controller.

AB - Neural network (NNs) approach for controlling switching power converters has been investigated in this paper. Several NNs techniques including the Back propagation training algorithm, Back propagation with momentum, Back propagation with adaptive learning rate and the Back propagation with Levenberg Marquardt optimisation have been investigated and the most later method has been selected for identification and control of Quasi-Resonant Converters (QRCs). A neural network emulator is designed in this paper, which reproduce the converter dynamic behaviour with great accuracy. The NN controller is developed and applied to regulate the converter output voltage. Results obtained from the NNC proved the validity and fast dynamic response of the proposed controller.

M3 - Conference contribution with ISSN or ISBN

SN - 0780371089

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EP - 2104

BT - Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society

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Eskander MN, Baha B. Identification and control of resonant switch mode converters using neural networks. In Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society. IEEE. 2001. p. 2099-2104