Model-Free design of control systems over wireless fading channels

Lima, Vinicius; Eisen, Mark; Gatsis, Konstantinos; Ribeiro, Alejandro

doi:10.1016/j.sigpro.2022.108540

Cited by 8 publications

(2 citation statements)

References 28 publications

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“…In order to address this problem, native AI methods have been used, using artificial neural networks to acquire knowledge on both the control and transmission scheduling signals [42]. It is important to mention that the DRL-based algorithms are independent of models and are used in real-world WNCS scenarios where precise understanding of the nonlinear system models is not necessary [43]. In contrast, traditional solutions rely only on model-based approaches.…”

Section: A Native Aimentioning

confidence: 99%

Toward Natively Intelligent Semantic Communications and Networking

Trevlakis,

Pappas,

Boulogeorgos

2024

IEEE Open J. Commun. Soc.

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As the process of envisioning, researching, and strategizing for 6G communications has commenced, we present our vision on the role of semantic communications (SemCom) in the beyond 5G era. In the following discourse, we delve into the factors that may impede the progress of research and implementation of 6G with the objective of catering to the semantically enriched communication requirements of the 2030s. In addition, we proceed to establish the fundamental attributes of SemCom and engage in an examination of the requisite technological modalities. In order to bolster this overarching vision, we introduce a semantic networking architecture that encapsulates and characterizes various application scenarios of SemCom. Expanding on the concept of point-to-point SemCom systems the semantic networking architecture focuses on extracting and filtering goal specific semantic information at the source before transmitting signals. It also involves decoding and post processing semantics at the destination. What sets this networking architecture apart is its transformation into a multi-user distributed, edge-to-cloud network with deadline constraint traffic. Given its complexity, implementing such an architecture necessitates frameworks for extracting and representing knowledge theoretical models to predict and manage multiple time varying deadline/delay constrained traffic flows that may cause significant congestion in the network as well, as innovative metrics infused with semantics to measure performance while encapsulating its inherent relevance. Finally, we provide research considerations and future directions towards the integration of semantics in the forthcoming 6G wireless systems.

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Section: A Native Aimentioning

confidence: 99%

Toward Natively Intelligent Semantic Communications and Networking

Trevlakis,

Pappas,

Boulogeorgos

2024

IEEE Open J. Commun. Soc.

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“…The resulting system model falls in the category of Markovian jump systems (MJSs), see Oswaldo Luiz Valle-do Costa (2005) and Vargas and Acho (2022). If the communication mode of an NCS is directly detectable, then the NCS can be treated as a time-varying system by considering the mode as a varying but known parameter (Bengtsson and Wik, 2022;Ding, 2014;Ding et al, 2011;Lima et al, 2022). Otherwise, it is needed to use extended methods for control (Haghighi and Tavassoli, 2021;Tavassoli et al, 2010;Zhang et al, 2017), filtering (Li et al, 2020;Xu et al, 2021) or identification of the NCSs (Cheng et al, 2020;Ding and Ding, 2010;Li and Zhang, 2022).…”

Section: Introductionmentioning

confidence: 99%

System identification in presence of undetectable packet losses in the actuation path

Mohammadzadeh,

Tavassoli

2023

Transactions of the Institute of Measurement and Control

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Identification of networked systems over communication links with packet losses is considered. It is assumed that there is no connection from the actuators to the system identifier such that no information is available on loss of data packets carrying the actuation signals. While the packet loss occurrences in the sensor links are naturally detectable by the system identifier as the receiving node, the packet loss occurrences in the actuation paths are not directly detectable. The existing system identification methods fail to be applicable without the information on packet loss occurrences. Presenting a solution for this issue is the objective of the present work. Two recursive algorithms are proposed to solve the problem in real time. For this purpose, ARMAX input–output representations of the system with Markovian jumping modes are developed. Then, filters are designed for estimation of the packet loss occurrences. The estimated mode is used in the recursive algorithms for identification of the whole system based on the maximum likelihood approach. A main algorithm and its simplified version are proposed that are capable of finding the various kinds of system parameters including the physical plant parameters and the communication mode transition probabilities. Effectiveness of the algorithms is verified through simulation examples where the system performance is evaluated and compared.

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