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Adaptive PIP control with application to greenhouse systems and dynamic traffic management

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Adaptive PIP control with application to greenhouse systems and dynamic traffic management. / Taylor, James; Chotai, Arunkumar.
IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176. Institution of Electrical Engineers (IEE), 1997.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Taylor, J & Chotai, A 1997, Adaptive PIP control with application to greenhouse systems and dynamic traffic management. in IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176. Institution of Electrical Engineers (IEE). https://doi.org/10.1049/ic:19970951

APA

Taylor, J., & Chotai, A. (1997). Adaptive PIP control with application to greenhouse systems and dynamic traffic management. In IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176 Institution of Electrical Engineers (IEE). https://doi.org/10.1049/ic:19970951

Vancouver

Taylor J, Chotai A. Adaptive PIP control with application to greenhouse systems and dynamic traffic management. In IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176. Institution of Electrical Engineers (IEE). 1997 doi: 10.1049/ic:19970951

Author

Taylor, James ; Chotai, Arunkumar. / Adaptive PIP control with application to greenhouse systems and dynamic traffic management. IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176. Institution of Electrical Engineers (IEE), 1997.

Bibtex

@inproceedings{007847deb0604f7d8e4c56f4429ed977,
title = "Adaptive PIP control with application to greenhouse systems and dynamic traffic management",
abstract = "Proportional-Integral-Plus (PIP) controllers, based on Non-Minimal State-Space (NMSS) design methods have been successfully implemented in a number of difficult applications including, for example, the self-adaptive control of a non-linear temperature control system; control of glasshouse micro-climate; multivariable decoupling of a realistic high order, non-linear simulation model of the Harrier VSTOL aircraft at its most difficult flight condition; and the control of various agricultural crop growth and plant physiology experiments. The present short paper concentrates on adaptive versions of the controllers, where the identification and estimation of the control model exploits the special properties of the recursive Simplified Refined Instrumental Variable (SRIV) algorithm. To exemplify the methodology, two rather different non-linear systems are considered: in the first place, adaptive multivariable control of greenhouse micro-climate; and secondly, the adaptive control of flow dynamics on interurban traffic networks.",
author = "James Taylor and Arunkumar Chotai",
year = "1997",
month = apr,
day = "10",
doi = "10.1049/ic:19970951",
language = "English",
booktitle = "IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176",
publisher = "Institution of Electrical Engineers (IEE)",
address = "United Kingdom",

}

RIS

TY - GEN

T1 - Adaptive PIP control with application to greenhouse systems and dynamic traffic management

AU - Taylor, James

AU - Chotai, Arunkumar

PY - 1997/4/10

Y1 - 1997/4/10

N2 - Proportional-Integral-Plus (PIP) controllers, based on Non-Minimal State-Space (NMSS) design methods have been successfully implemented in a number of difficult applications including, for example, the self-adaptive control of a non-linear temperature control system; control of glasshouse micro-climate; multivariable decoupling of a realistic high order, non-linear simulation model of the Harrier VSTOL aircraft at its most difficult flight condition; and the control of various agricultural crop growth and plant physiology experiments. The present short paper concentrates on adaptive versions of the controllers, where the identification and estimation of the control model exploits the special properties of the recursive Simplified Refined Instrumental Variable (SRIV) algorithm. To exemplify the methodology, two rather different non-linear systems are considered: in the first place, adaptive multivariable control of greenhouse micro-climate; and secondly, the adaptive control of flow dynamics on interurban traffic networks.

AB - Proportional-Integral-Plus (PIP) controllers, based on Non-Minimal State-Space (NMSS) design methods have been successfully implemented in a number of difficult applications including, for example, the self-adaptive control of a non-linear temperature control system; control of glasshouse micro-climate; multivariable decoupling of a realistic high order, non-linear simulation model of the Harrier VSTOL aircraft at its most difficult flight condition; and the control of various agricultural crop growth and plant physiology experiments. The present short paper concentrates on adaptive versions of the controllers, where the identification and estimation of the control model exploits the special properties of the recursive Simplified Refined Instrumental Variable (SRIV) algorithm. To exemplify the methodology, two rather different non-linear systems are considered: in the first place, adaptive multivariable control of greenhouse micro-climate; and secondly, the adaptive control of flow dynamics on interurban traffic networks.

U2 - 10.1049/ic:19970951

DO - 10.1049/ic:19970951

M3 - Conference contribution/Paper

BT - IEE Colloquium on Adaptive Controllers in Practice, Digest No 97/176

PB - Institution of Electrical Engineers (IEE)

ER -