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Linear and nonlinear non-minimal state space control system design.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

Published

Standard

Linear and nonlinear non-minimal state space control system design. / Taylor, C. J.; Chotai, A.; Tych, W.

System Identification, Environmental Modelling and Control System Design. ed. / L. Wang; H. Garnier. London : Springer, 2012. p. 559-582.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

Harvard

Taylor, CJ, Chotai, A & Tych, W 2012, Linear and nonlinear non-minimal state space control system design. in L Wang & H Garnier (eds), System Identification, Environmental Modelling and Control System Design. Springer, London, pp. 559-582. https://doi.org/10.1007/978-0-85729-974-1

APA

Taylor, C. J., Chotai, A., & Tych, W. (2012). Linear and nonlinear non-minimal state space control system design. In L. Wang, & H. Garnier (Eds.), System Identification, Environmental Modelling and Control System Design (pp. 559-582). Springer. https://doi.org/10.1007/978-0-85729-974-1

Vancouver

Taylor CJ, Chotai A, Tych W. Linear and nonlinear non-minimal state space control system design. In Wang L, Garnier H, editors, System Identification, Environmental Modelling and Control System Design. London: Springer. 2012. p. 559-582 https://doi.org/10.1007/978-0-85729-974-1

Author

Taylor, C. J. ; Chotai, A. ; Tych, W. / Linear and nonlinear non-minimal state space control system design. System Identification, Environmental Modelling and Control System Design. editor / L. Wang ; H. Garnier. London : Springer, 2012. pp. 559-582

Bibtex

@inbook{8a784aeaad3a4e83aba73d964db40e86,
title = "Linear and nonlinear non-minimal state space control system design.",
abstract = "This tutorial chapter uses case studies based on recent engineering applications, to re-examine the non-minimal, state variable feedback approach to control system design. We show how the non-minimal state space (NMSS) representation seems to be the natural description of a discrete-time Transfer Function, since its dimension is dictated by the complete structure of the model. This is in contrast to minimal state space descriptions, which only account for the order of the denominator and whose state variables, therefore, usually represent combinations of input and output signals. The resulting control algorithm can be interpreted as a logical extension of the conventional Proportional-Integral (PI) controller, facilitating its straightforward implementation using a standard hardware-software arrangement. Finally, the basic NMSS approach is readily extended into multivariable, model-predictive and nonlinear control systems, hence the chapter briefly discusses these areas and gives pointers to the latest research results.",
author = "Taylor, {C. J.} and A. Chotai and W. Tych",
year = "2012",
doi = "10.1007/978-0-85729-974-1",
language = "English",
isbn = "978-0857299734",
pages = "559--582",
editor = "L. Wang and H. Garnier",
booktitle = "System Identification, Environmental Modelling and Control System Design",
publisher = "Springer",

}

RIS

TY - CHAP

T1 - Linear and nonlinear non-minimal state space control system design.

AU - Taylor, C. J.

AU - Chotai, A.

AU - Tych, W.

PY - 2012

Y1 - 2012

N2 - This tutorial chapter uses case studies based on recent engineering applications, to re-examine the non-minimal, state variable feedback approach to control system design. We show how the non-minimal state space (NMSS) representation seems to be the natural description of a discrete-time Transfer Function, since its dimension is dictated by the complete structure of the model. This is in contrast to minimal state space descriptions, which only account for the order of the denominator and whose state variables, therefore, usually represent combinations of input and output signals. The resulting control algorithm can be interpreted as a logical extension of the conventional Proportional-Integral (PI) controller, facilitating its straightforward implementation using a standard hardware-software arrangement. Finally, the basic NMSS approach is readily extended into multivariable, model-predictive and nonlinear control systems, hence the chapter briefly discusses these areas and gives pointers to the latest research results.

AB - This tutorial chapter uses case studies based on recent engineering applications, to re-examine the non-minimal, state variable feedback approach to control system design. We show how the non-minimal state space (NMSS) representation seems to be the natural description of a discrete-time Transfer Function, since its dimension is dictated by the complete structure of the model. This is in contrast to minimal state space descriptions, which only account for the order of the denominator and whose state variables, therefore, usually represent combinations of input and output signals. The resulting control algorithm can be interpreted as a logical extension of the conventional Proportional-Integral (PI) controller, facilitating its straightforward implementation using a standard hardware-software arrangement. Finally, the basic NMSS approach is readily extended into multivariable, model-predictive and nonlinear control systems, hence the chapter briefly discusses these areas and gives pointers to the latest research results.

U2 - 10.1007/978-0-85729-974-1

DO - 10.1007/978-0-85729-974-1

M3 - Chapter

SN - 978-0857299734

SP - 559

EP - 582

BT - System Identification, Environmental Modelling and Control System Design

A2 - Wang, L.

A2 - Garnier, H.

PB - Springer

CY - London

ER -