Indiscernible topological variations in DAE networks

Patil, Deepak U.; Tesi, Pietro; Trenn, Stephan

doi:10.1016/j.automatica.2018.12.012

Cited by 17 publications

(18 citation statements)

References 15 publications

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“…For example, it is shown in [4] that even if the transfer function matrix (TFM) of an NDS can be perfectly estimated, there are still possibilities that its subsystem interactions can not be identified. To clarify situations under which NDS structure can be identified, some eigenvector based conditions are derived in [10] for an NDS with descriptor subsystems and diffusive subsystem coupling, so that variations of its subsystem interactions can be detected. [18] studies topology identifiability when subsystems of an NDS are coupled through their outputs.…”

Section: Introductionmentioning

confidence: 99%

Structure Identifiability of an NDS with LFT Parametrized Subsystems

Zhou

2020

Preprint

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Requirements on subsystems have been made clear in this paper for a linear time invariant (LTI) networked dynamic system (NDS), under which subsystem interconnections can be estimated from external output measurements. In this NDS, subsystems may have distinctive dynamics, and subsystem interconnections are arbitrary. It is assumed that system matrices of each subsystem depend on its (pseudo) first principle parameters (FPPs) through a linear fractional transformation (LFT). It has been proven that if in each subsystem, the transfer function matrix (TFM) from its internal inputs to its external outputs is of full normal column rank (FNCR), while the TFM from its external inputs to its internal outputs is of full normal row rank (FNRR), then the NDS is structurally identifiable. Moreover, under some particular situations like there are no direct information transmission from an internal input to an internal output in each subsystem, a necessary and sufficient condition is established for NDS structure identifiability. A matrix valued polynomial (MVP) rank based equivalent condition is further derived, which depends affinely on subsystem (pseudo) FPPs and can be independently verified for each subsystem. From this condition, some necessary conditions are obtained for both subsystem dynamics and its (pseudo) FPPs, using the Kronecker canonical form (KCF) of a matrix pencil.

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Section: Introductionmentioning

confidence: 99%

Structure Identifiability of an NDS with LFT Parametrized Subsystems

Zhou

2020

Preprint

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“…Compared with the results of [16,17], the conditions of Sections 3 and 4 are both necessary and sufficient. In addition, they do not ask that the internal output vector of each subsystem is identically equal to its external one.…”

Section: Some Particular Situationsmentioning

confidence: 92%

“…Nevertheless, it is still a challenging issue even for a lumped LTI system [1,8,9,14,21]. As structure information is widely recognized to be quite important in NDS analysis and synthesis, structure identifiability is used throughout this paper, in order to reflect this importance and to distinguish it from the traditional parameter identifiability, which is also adopted in other works, such as [13,14,16,17] and the references therein.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…Some necessary and sufficient conditions have been established there for the ability of reconstructing these dynamical structure functions from the TFM of the whole NDS. In terms of eigenvectors, [16] gives some necessary and sufficient conditions for detecting structure variations in an NDS with descriptor form subsystems and diffusive subsystem couplings. For an NDS with its subsystems being described by a state space model and coupled through their outputs, [17] proven that its structure is identifiable only when the constant kernel of a TFM is exactly the zero vector, which is completely determined by the dynamics of each subsystem.…”

Section: Introductionmentioning

confidence: 99%

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Global Structure Identifiability and Reconstructibility of an NDS with Descriptor Subsystems

Zhou,

Yin

2021

Preprint

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This paper investigates requirements on a networked dynamic system (NDS) such that its subsystem interactions can be solely determined from experiment data or reconstructed from its overall model. The NDS is constituted from several subsystems whose dynamics are described through a descriptor form. Except regularity on each subsystem and the whole NDS, no other restrictions are put on either subsystem dynamics or subsystem interactions. A matrix rank based necessary and sufficient condition is derived for the global identifiability of subsystem interactions, which leads to several conclusions about NDS structure identifiability when there is some a priori information. This matrix also gives an explicit description for the set of subsystem interactions that can not be distinguished from experiment data only. In addition, under a well-posedness assumption, a necessary and sufficient condition is obtained for the reconstructibility of subsystem interactions from an NDS descriptor form model. This condition can be verified with each subsystem separately and is therefore attractive in the analysis and synthesis of a large-scale NDS. Simulation results show that rather than increases monotonically with the distance of subsystem interactions to the undifferentiable set, the magnitude of the external output differences between two NDSs with distinct subsystem interactions increases much more rapidly when one of them is close to be unstable. In addition, directions of probing signals are also very important in distinguishing external outputs of distinctive NDSs. These findings are expected to be helpful in identification experiment designs, etc.

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“…On the other hand, in general, the problem of detecting an edge disconnection has been investigated for multi-agent systems that are not necessarily consensus networks. For instance, in [4] and [29] the possibility of detecting an edge or a node disconnection in a multi-agent system is investigated, and the concepts of discernibility from the states or the outputs are investigated. In [43] the problem of detecting an edge disconnection is addressed for a diffusive network, by resorting to an impulsive input applied at one specific node.…”

Section: Introductionmentioning

confidence: 99%

On the detection and identification of edge disconnections in a multi-agent consensus network

Parlangeli,

Valcher

2021

Preprint

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In this paper we investigate the problem of the sudden disconnection of an edge in a discrete-time multi-agent consensus network. If the graph remains strongly connected, the multi-agent system still achieves consensus, but in general, unless the information exchange between each pair of agents is symmetric, the agents' states converge to a drifted value of the original consensus value. Consequently the edge disconnection can go unnoticed. In this paper the problems of detecting an edge disconnection and of identifying in a finite number of steps the exact edge that got disconnected are investigated. Necessary and sufficient conditions for both problems to be solvable are presented, both in case all the agents' states are available and in case only a subset of the agents' states is measured. Finally, an example of a network of 7 agents is provided, to illustrate some of the theoretical results derived in the paper.

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Indiscernible topological variations in DAE networks

Cited by 17 publications

References 15 publications

Structure Identifiability of an NDS with LFT Parametrized Subsystems

Structure Identifiability of an NDS with LFT Parametrized Subsystems

Global Structure Identifiability and Reconstructibility of an NDS with Descriptor Subsystems

On the detection and identification of edge disconnections in a multi-agent consensus network

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