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State space control system design based on non-minimal state-variable feedback: further generalisation and unification results.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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State space control system design based on non-minimal state-variable feedback: further generalisation and unification results. / Taylor, C. James; Chotai, Arun; Young, Peter C.
In: International Journal of Control, Vol. 73, No. 14, 09.2000, p. 1329-1345.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Taylor, CJ, Chotai, A & Young, PC 2000, 'State space control system design based on non-minimal state-variable feedback: further generalisation and unification results.', International Journal of Control, vol. 73, no. 14, pp. 1329-1345. https://doi.org/10.1080/002071700421727

APA

Taylor, C. J., Chotai, A., & Young, P. C. (2000). State space control system design based on non-minimal state-variable feedback: further generalisation and unification results. International Journal of Control, 73(14), 1329-1345. https://doi.org/10.1080/002071700421727

Vancouver

Taylor CJ, Chotai A, Young PC. State space control system design based on non-minimal state-variable feedback: further generalisation and unification results. International Journal of Control. 2000 Sept;73(14):1329-1345. doi: 10.1080/002071700421727

Author

Taylor, C. James ; Chotai, Arun ; Young, Peter C. / State space control system design based on non-minimal state-variable feedback: further generalisation and unification results. In: International Journal of Control. 2000 ; Vol. 73, No. 14. pp. 1329-1345.

Bibtex

@article{32191a8de6634298a4e8dcebad0aad1e,
title = "State space control system design based on non-minimal state-variable feedback: further generalisation and unification results.",
abstract = "This paper shows how proportional-integral-plus linear-quadratic (PIP-LQ) control, based on non-minimal state space (NMSS) control system design, can be constrained to yield exactly the same control algorithm as both generalized predictive control (GPC) and standard, minimal state, linear quadratic gaussian (LQG) design methods. However, while NMSS includes these other approaches as special cases, it is less constrained and so more flexible in general terms: for example, while PIP-LQ has the simplicity of GPC, it is formulated like LQG in the powerful context of state variable feedback (SVF) control, which allows for ready access to modern robust control methods. Furthermore, the paper suggests that the NMSS approach provides the greater design freedom, with a wider range of possible LQ solutions than its minimal state space equivalent.",
keywords = "non-minimal state space, linear-quadratic, generalized predictive control, proportional-integral-plus",
author = "Taylor, {C. James} and Arun Chotai and Young, {Peter C.}",
year = "2000",
month = sep,
doi = "10.1080/002071700421727",
language = "English",
volume = "73",
pages = "1329--1345",
journal = "International Journal of Control",
issn = "0020-7179",
publisher = "Taylor and Francis Ltd.",
number = "14",

}

RIS

TY - JOUR

T1 - State space control system design based on non-minimal state-variable feedback: further generalisation and unification results.

AU - Taylor, C. James

AU - Chotai, Arun

AU - Young, Peter C.

PY - 2000/9

Y1 - 2000/9

N2 - This paper shows how proportional-integral-plus linear-quadratic (PIP-LQ) control, based on non-minimal state space (NMSS) control system design, can be constrained to yield exactly the same control algorithm as both generalized predictive control (GPC) and standard, minimal state, linear quadratic gaussian (LQG) design methods. However, while NMSS includes these other approaches as special cases, it is less constrained and so more flexible in general terms: for example, while PIP-LQ has the simplicity of GPC, it is formulated like LQG in the powerful context of state variable feedback (SVF) control, which allows for ready access to modern robust control methods. Furthermore, the paper suggests that the NMSS approach provides the greater design freedom, with a wider range of possible LQ solutions than its minimal state space equivalent.

AB - This paper shows how proportional-integral-plus linear-quadratic (PIP-LQ) control, based on non-minimal state space (NMSS) control system design, can be constrained to yield exactly the same control algorithm as both generalized predictive control (GPC) and standard, minimal state, linear quadratic gaussian (LQG) design methods. However, while NMSS includes these other approaches as special cases, it is less constrained and so more flexible in general terms: for example, while PIP-LQ has the simplicity of GPC, it is formulated like LQG in the powerful context of state variable feedback (SVF) control, which allows for ready access to modern robust control methods. Furthermore, the paper suggests that the NMSS approach provides the greater design freedom, with a wider range of possible LQ solutions than its minimal state space equivalent.

KW - non-minimal state space

KW - linear-quadratic

KW - generalized predictive control

KW - proportional-integral-plus

U2 - 10.1080/002071700421727

DO - 10.1080/002071700421727

M3 - Journal article

VL - 73

SP - 1329

EP - 1345

JO - International Journal of Control

JF - International Journal of Control

SN - 0020-7179

IS - 14

ER -