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Proportional-integral-plus (PIP) design for stochastic delta operator systems

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Proportional-integral-plus (PIP) design for stochastic delta operator systems. / Chotai, A.; Young, P. C.; Tych, W. et al.
In: IEE Conference Publication, Vol. 1, No. 389, 1994, p. 75-80.

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

Harvard

Chotai, A, Young, PC, Tych, W & Lees, M 1994, 'Proportional-integral-plus (PIP) design for stochastic delta operator systems', IEE Conference Publication, vol. 1, no. 389, pp. 75-80. https://doi.org/10.1049/cp:19940112

APA

Chotai, A., Young, P. C., Tych, W., & Lees, M. (1994). Proportional-integral-plus (PIP) design for stochastic delta operator systems. IEE Conference Publication, 1(389), 75-80. https://doi.org/10.1049/cp:19940112

Vancouver

Chotai A, Young PC, Tych W, Lees M. Proportional-integral-plus (PIP) design for stochastic delta operator systems. IEE Conference Publication. 1994;1(389):75-80. doi: 10.1049/cp:19940112

Author

Chotai, A. ; Young, P. C. ; Tych, W. et al. / Proportional-integral-plus (PIP) design for stochastic delta operator systems. In: IEE Conference Publication. 1994 ; Vol. 1, No. 389. pp. 75-80.

Bibtex

@article{9382bd101d7b4a96a145cf25d79b9aa0,
title = "Proportional-integral-plus (PIP) design for stochastic delta operator systems",
abstract = "The paper shows how Proportional-Integral-Plus (PIP) control system design for rapidly sampled systems described by delta (δ) operator transfer function models is based on the formulation of a special Non-Minimum State Space (NMSS) representation, whose state variables are the discrete-time derivatives of the output and input signals. The stochastic version of this model provides the basis for Linear Quadratic Gaussian (LQG) control system design in the δ domain. As in the more conventional minimum state space situation, the state variable feedback PIP control law is obtained straightforwardly by the introduction of a Kalman filter and the application of the separation principle. Although the resulting PIP control system is simple to implement, its exploitation of state variable feedback (SVF) ensures the power and flexibility of its operation.",
author = "A. Chotai and Young, {P. C.} and W. Tych and M. Lees",
year = "1994",
doi = "10.1049/cp:19940112",
language = "English",
volume = "1",
pages = "75--80",
journal = "IEE Conference Publication",
issn = "0537-9989",
publisher = "Institution of Engineering and Technology",
number = "389",
note = "Proceedings of the International Conference on CONTROL '94. Part 1 (of 2) ; Conference date: 21-03-1994 Through 24-03-1994",

}

RIS

TY - JOUR

T1 - Proportional-integral-plus (PIP) design for stochastic delta operator systems

AU - Chotai, A.

AU - Young, P. C.

AU - Tych, W.

AU - Lees, M.

PY - 1994

Y1 - 1994

N2 - The paper shows how Proportional-Integral-Plus (PIP) control system design for rapidly sampled systems described by delta (δ) operator transfer function models is based on the formulation of a special Non-Minimum State Space (NMSS) representation, whose state variables are the discrete-time derivatives of the output and input signals. The stochastic version of this model provides the basis for Linear Quadratic Gaussian (LQG) control system design in the δ domain. As in the more conventional minimum state space situation, the state variable feedback PIP control law is obtained straightforwardly by the introduction of a Kalman filter and the application of the separation principle. Although the resulting PIP control system is simple to implement, its exploitation of state variable feedback (SVF) ensures the power and flexibility of its operation.

AB - The paper shows how Proportional-Integral-Plus (PIP) control system design for rapidly sampled systems described by delta (δ) operator transfer function models is based on the formulation of a special Non-Minimum State Space (NMSS) representation, whose state variables are the discrete-time derivatives of the output and input signals. The stochastic version of this model provides the basis for Linear Quadratic Gaussian (LQG) control system design in the δ domain. As in the more conventional minimum state space situation, the state variable feedback PIP control law is obtained straightforwardly by the introduction of a Kalman filter and the application of the separation principle. Although the resulting PIP control system is simple to implement, its exploitation of state variable feedback (SVF) ensures the power and flexibility of its operation.

UR - http://www.scopus.com/inward/record.url?scp=0028131094&partnerID=8YFLogxK

U2 - 10.1049/cp:19940112

DO - 10.1049/cp:19940112

M3 - Conference article

AN - SCOPUS:0028131094

VL - 1

SP - 75

EP - 80

JO - IEE Conference Publication

JF - IEE Conference Publication

SN - 0537-9989

IS - 389

T2 - Proceedings of the International Conference on CONTROL '94. Part 1 (of 2)

Y2 - 21 March 1994 through 24 March 1994

ER -