Randa Herzallah
A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise
Herzallah, Randa; Zhou, Yuyang
Abstract
This article proposes the exploitation of the Kullback–Leibler divergence to characterise the uncertainty of the tracking error for general stochastic systems without constraints of certain distributions. The general solution to the fully probabilistic design of the tracking error control problem is first stated. Further development then focuses on the derivation of a randomised controller for a class of linear stochastic Gaussian systems that are affected by multiplicative noise. The derived control solution takes the multiplicative noise of the controlled system into consideration in the derivation of the randomised controller. The proposed fully probabilistic design of the tracking error of the system dynamics is a more legitimate approach than the conventional fully probabilistic design method. It directly characterises the main objective of system control. The efficiency of the proposed method is then demonstrated on a flexible beam example where the vibration quenching in flexible beams is shown to be effectively suppressed.
Citation
Herzallah, R., & Zhou, Y. (2020). A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise. Journal of Vibration and Control, 26(23-24), 2329-2339. https://doi.org/10.1177/1077546320921608
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 8, 2020 |
Online Publication Date | Apr 17, 2020 |
Publication Date | 2020-12 |
Deposit Date | Nov 22, 2021 |
Publicly Available Date | Nov 22, 2021 |
Journal | Journal of Vibration and Control |
Print ISSN | 1077-5463 |
Electronic ISSN | 1741-2986 |
Publisher | SAGE Publications |
Peer Reviewed | Peer Reviewed |
Volume | 26 |
Issue | 23-24 |
Pages | 2329-2339 |
DOI | https://doi.org/10.1177/1077546320921608 |
Public URL | http://researchrepository.napier.ac.uk/Output/2817832 |
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Copyright Statement
This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed.
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