Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

Yuyang Zhou; Randa Herzallah; Ana Zafar

doi:10.1109/ICCA.2019.8899607

Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

Yuyang Zhou
, Randa Herzallah
, Ana Zafar

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

6 Citations (Scopus)

83 Downloads (Pure)

Abstract

In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared
with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.

Original language	English
Title of host publication	2019 IEEE 15th International Conference on Control and Automation, ICCA 2019
Publisher	IEEE
Pages	940-945
Number of pages	6
ISBN (Electronic)	9781728111643
DOIs	https://doi.org/10.1109/ICCA.2019.8899607
Publication status	Published - 19 Jul 2019
Event	The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019) - Duration: 16 Jul 2019 → … http://uav.ece.nus.edu.sg/~icca19/call_for_paper.html

Conference

Conference	The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019)
Period	16/07/19 → …
Internet address	http://uav.ece.nus.edu.sg/~icca19/call_for_paper.html

Bibliographical note

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Access to Document

10.1109/ICCA.2019.8899607

Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Submitted manuscript, 198 KB

Cite this

@inproceedings{7d8e960e52f846729a13b70cb434ddb9,

title = "Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise",

abstract = "In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.",

author = "Yuyang Zhou and Randa Herzallah and Ana Zafar",

note = "{\textcopyright} 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019) ; Conference date: 16-07-2019",

year = "2019",

month = jul,

day = "19",

doi = "10.1109/ICCA.2019.8899607",

language = "English",

pages = "940--945",

booktitle = "2019 IEEE 15th International Conference on Control and Automation, ICCA 2019",

publisher = "IEEE",

address = "United States",

url = "http://uav.ece.nus.edu.sg/\textasciitilde{}icca19/call\_for\_paper.html",

}

TY - GEN

T1 - Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

AU - Zhou, Yuyang

AU - Herzallah, Randa

AU - Zafar, Ana

N1 - © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2019/7/19

Y1 - 2019/7/19

N2 - In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.

AB - In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.

UR - http://www.ieee-icca.org/

UR - https://www.scopus.com/pages/publications/85075774637

U2 - 10.1109/ICCA.2019.8899607

DO - 10.1109/ICCA.2019.8899607

M3 - Conference publication

SP - 940

EP - 945

BT - 2019 IEEE 15th International Conference on Control and Automation, ICCA 2019

PB - IEEE

T2 - The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019)

Y2 - 16 July 2019

ER -

Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

Abstract

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this