Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks

Linyao Wu; Yumin Zhang; Tao Ma; Lei Guo

Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks

Linyao Wu
, Yumin Zhang
, Tao Ma
, Lei Guo^*

^*Corresponding author for this work

Southeast University, Nanjing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper considers the robust tracking control problem for output stochastic distributions of dynamic non-Gaussian systems. By using the square root B-spline approximations with modelling errors, a robust constrained tracking control strategy with proportional-integral (PI) structure is investigated for a nonlinear weighting system in the presence of exogenous disturbances. The main objective is to make the output probability density functions (PDFs) to follow a target PDF. An LMI-based PI control algorithm is proposed to track the desired weight dynamics, where the robust peak-to-peak measure is applied to optimize the tracking performance and the state constraints system related to the B-Spline expansion can be guaranteed. Rigorous stability and performance analysis is provided for the constrained weight tracking control problem.

Original language	English
Title of host publication	Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Pages	1831-1835
Number of pages	5
State	Published - 2005
Externally published	Yes
Event	2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 - Beijing, China Duration: 13 Oct 2005 → 15 Oct 2005

Publication series

Name	Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Volume	3

Conference

Conference	2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
Country/Territory	China
City	Beijing
Period	13/10/05 → 15/10/05

Cite this

Wu, L., Zhang, Y., Ma, T., & Guo, L. (2005). Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks. In Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 (pp. 1831-1835). Article 1614982 (Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05; Vol. 3).

Wu, Linyao ; Zhang, Yumin ; Ma, Tao et al. / Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks. Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05. 2005. pp. 1831-1835 (Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05).

@inproceedings{6a3f0348e989401b853febfed5cfc8c2,

title = "Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks",

abstract = "This paper considers the robust tracking control problem for output stochastic distributions of dynamic non-Gaussian systems. By using the square root B-spline approximations with modelling errors, a robust constrained tracking control strategy with proportional-integral (PI) structure is investigated for a nonlinear weighting system in the presence of exogenous disturbances. The main objective is to make the output probability density functions (PDFs) to follow a target PDF. An LMI-based PI control algorithm is proposed to track the desired weight dynamics, where the robust peak-to-peak measure is applied to optimize the tracking performance and the state constraints system related to the B-Spline expansion can be guaranteed. Rigorous stability and performance analysis is provided for the constrained weight tracking control problem.",

author = "Linyao Wu and Yumin Zhang and Tao Ma and Lei Guo",

year = "2005",

language = "英语",

isbn = "0780394224",

series = "Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05",

pages = "1831--1835",

booktitle = "Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05",

note = "2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05 ; Conference date: 13-10-2005 Through 15-10-2005",

}

Wu, L, Zhang, Y, Ma, T & Guo, L 2005, Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks. in Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05., 1614982, Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05, vol. 3, pp. 1831-1835, 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05, Beijing, China, 13/10/05.

Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks. / Wu, Linyao; Zhang, Yumin; Ma, Tao et al.
Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05. 2005. p. 1831-1835 1614982 (Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks

AU - Wu, Linyao

AU - Zhang, Yumin

AU - Ma, Tao

AU - Guo, Lei

PY - 2005

Y1 - 2005

N2 - This paper considers the robust tracking control problem for output stochastic distributions of dynamic non-Gaussian systems. By using the square root B-spline approximations with modelling errors, a robust constrained tracking control strategy with proportional-integral (PI) structure is investigated for a nonlinear weighting system in the presence of exogenous disturbances. The main objective is to make the output probability density functions (PDFs) to follow a target PDF. An LMI-based PI control algorithm is proposed to track the desired weight dynamics, where the robust peak-to-peak measure is applied to optimize the tracking performance and the state constraints system related to the B-Spline expansion can be guaranteed. Rigorous stability and performance analysis is provided for the constrained weight tracking control problem.

AB - This paper considers the robust tracking control problem for output stochastic distributions of dynamic non-Gaussian systems. By using the square root B-spline approximations with modelling errors, a robust constrained tracking control strategy with proportional-integral (PI) structure is investigated for a nonlinear weighting system in the presence of exogenous disturbances. The main objective is to make the output probability density functions (PDFs) to follow a target PDF. An LMI-based PI control algorithm is proposed to track the desired weight dynamics, where the robust peak-to-peak measure is applied to optimize the tracking performance and the state constraints system related to the B-Spline expansion can be guaranteed. Rigorous stability and performance analysis is provided for the constrained weight tracking control problem.

UR - https://www.scopus.com/pages/publications/33847119380

M3 - 会议稿件

AN - SCOPUS:33847119380

SN - 0780394224

SN - 9780780394223

T3 - Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

SP - 1831

EP - 1835

BT - Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

T2 - 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

Y2 - 13 October 2005 through 15 October 2005

ER -

Robust PI tracking strategy for output probability distributions based on uncertain B-spline neural networks

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