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Decentralised fully probabilistic design for stochastic networks with multiplicative noise
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Zhou, Yuyang, Herzallah, Randa and Zhang, Qichun (2023) Decentralised fully probabilistic design for stochastic networks with multiplicative noise. International Journal Of Systems Science, 54 (8). pp. 1841-1854. doi:10.1080/00207721.2023.2210568 ISSN 0020-7721.
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WRAP-decentralised-fully-probabilistic-design-stochastic-networks-multiplicative noise-Herzallah-2023.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1743Kb) | Preview |
Official URL: https://doi.org/10.1080/00207721.2023.2210568
Abstract
In this paper, we present an innovative decentralised control framework, designed to address stochastic dynamic complex systems that are influenced by multiple multiplicative noise factors. Our advanced approach builds upon the foundation of conventional Decentralised Fully Probabilistic Design (DFPD)byrefiningtheRiccatiequationtoaccommodatemultiplenoisesourceseffectively. By embracing the inherent stochastic nature of complex systems, our methodology fully characterizes their dynamic behaviours using probabilistic state–space models, delivering a comprehensive representation of subsystem components. Importantly, the DFPD approach also incorporates system and input constraints by characterising their corresponding ideal distributions, ensuring optimal functionality and performance while adhering to permissible boundaries. To further enhance system performance, we introduce a probabilistic message passing architecture that enables seamless communication between neighbouring subsystems and promotes harmonised decision-making among local nodes. To demonstrate the efficacy of our proposed framework, we employ a three-inverted pendulum system as a numerical example and compare its performance to that of the conventional DFPD. Through this comparison, we showcase the advantages of our novel decentralised control approach in handling complex systems with multiple noise factors.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics | ||||||||
| Library of Congress Subject Headings (LCSH): | Stochastic control theory, Stochastic systems, Engineering design, Noise | ||||||||
| Journal or Publication Title: | International Journal Of Systems Science | ||||||||
| Publisher: | Taylor and Francis Online | ||||||||
| ISSN: | 0020-7721 | ||||||||
| Official Date: | 2023 | ||||||||
| Dates: |
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| Volume: | 54 | ||||||||
| Number: | 8 | ||||||||
| Page Range: | pp. 1841-1854 | ||||||||
| DOI: | 10.1080/00207721.2023.2210568 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||
| Date of first compliant deposit: | 7 June 2023 | ||||||||
| Date of first compliant Open Access: | 8 June 2023 |
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