Iterative learning control of output PDF shaping in stochastic systems

H. Wang; J.F. Zhang; H. Yue

doi:10.1109/.2005.1467189

Iterative learning control of output PDF shaping in stochastic systems

H. Wang, J.F. Zhang, H. Yue

Electronic And Electrical Engineering

Research output: Contribution to conference › Proceeding › peer-review

14 Citations (Scopus)

Abstract

An iterative learning control (ILC) algorithm has been proposed for the shaping of the output probability density function (PDF) of non-Gaussian stochastic systems. Based on the B-spline modeling of the output PDF, the control strategy is implemented in three steps at each iterative batch. Firstly, the distance between the output PDF of the system and the desired PDF is used between each batch to adjust the B-spline functions. The parameters of the B-spline based PDF model are then identified accordingly. Finally, the control input is designed by optimising a quadratic integral performance function within each batch

Original language	English
Pages	1225 - 1230
Number of pages	6
DOIs	https://doi.org/10.1109/.2005.1467189
Publication status	Published - Jun 2005
Event	20th IEEE International Symposium on Intelligent Control (ISIC ‘05)/13th Mediterranean Conference on Control and Automation (MED ’05) - , Cyprus Duration: 27 Jun 2005 → 29 Jun 2005

Conference

Conference	20th IEEE International Symposium on Intelligent Control (ISIC ‘05)/13th Mediterranean Conference on Control and Automation (MED ’05)
Country/Territory	Cyprus
Period	27/06/05 → 29/06/05

Keywords

iterative
learning control
output
pdf
shaping
stochastic systems

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10.1109/.2005.1467189

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title = "Iterative learning control of output PDF shaping in stochastic systems",

abstract = "An iterative learning control (ILC) algorithm has been proposed for the shaping of the output probability density function (PDF) of non-Gaussian stochastic systems. Based on the B-spline modeling of the output PDF, the control strategy is implemented in three steps at each iterative batch. Firstly, the distance between the output PDF of the system and the desired PDF is used between each batch to adjust the B-spline functions. The parameters of the B-spline based PDF model are then identified accordingly. Finally, the control input is designed by optimising a quadratic integral performance function within each batch ",

keywords = "iterative , learning control, output, pdf, shaping, stochastic systems",

author = "H. Wang and J.F. Zhang and H. Yue",

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AU - Wang, H.

AU - Zhang, J.F.

AU - Yue, H.

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N2 - An iterative learning control (ILC) algorithm has been proposed for the shaping of the output probability density function (PDF) of non-Gaussian stochastic systems. Based on the B-spline modeling of the output PDF, the control strategy is implemented in three steps at each iterative batch. Firstly, the distance between the output PDF of the system and the desired PDF is used between each batch to adjust the B-spline functions. The parameters of the B-spline based PDF model are then identified accordingly. Finally, the control input is designed by optimising a quadratic integral performance function within each batch

AB - An iterative learning control (ILC) algorithm has been proposed for the shaping of the output probability density function (PDF) of non-Gaussian stochastic systems. Based on the B-spline modeling of the output PDF, the control strategy is implemented in three steps at each iterative batch. Firstly, the distance between the output PDF of the system and the desired PDF is used between each batch to adjust the B-spline functions. The parameters of the B-spline based PDF model are then identified accordingly. Finally, the control input is designed by optimising a quadratic integral performance function within each batch

KW - iterative

KW - learning control

KW - output

KW - pdf

KW - shaping

KW - stochastic systems

U2 - 10.1109/.2005.1467189

DO - 10.1109/.2005.1467189

M3 - Proceeding

SP - 1225

EP - 1230

T2 - 20th IEEE International Symposium on Intelligent Control (ISIC ‘05)/13th Mediterranean Conference on Control and Automation (MED ’05)

Y2 - 27 June 2005 through 29 June 2005

ER -

Iterative learning control of output PDF shaping in stochastic systems

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