Networked Estimation of Relative Sensing Multiagent Systems Using Reconfigurable Sets of Subobservers

Azizi, S. Mohsen; Khorasani, K.

doi:10.1109/tcst.2014.2300198

Cited by 13 publications

(9 citation statements)

References 43 publications

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“…For another type of actuator fault, namely the loss-of-effectiveness (LOE) fault [11], which is regarded as a multiplicative fault, the overall fault-augmented system model becomes bilinear. This type of multiplicative fault has already been studied by the authors in [6] and [7] and is therefore beyond the scope of the class of multi-agent systems considered in this paper. Finally, this paper considers only faults that have already progressed to a certain level of severity to be regarded as anomalies or failures, and hence the case of incipient (slowly developing) faults is also not studied here.…”

Section: Fault-augmented State Space Model Of Multi-agent Systemsmentioning

confidence: 99%

“…The sub-observer #i in (7) corresponds to the partition of the system (5). This partitioning is accomplished by following the same steps as in the Procedure 1 and is represented by the linear time-invariant (LTI) model…”

Section: Sub-observer Design Proceduresmentioning

confidence: 99%

“…It should be noted that X (i) represents the state vector of the sub-system #i (in (11)), which corresponds to the state estimateX (i) of the sub-observer #i (in (7) or (10)), and which is different from X i that represents the state vector of the agent #i (in (1)).…”

Section: Sub-observer Design Proceduresmentioning

confidence: 99%

“…Consider the proposed networked subobservers that are governed by the dynamics (7) with the overall gain matrixK = diag(K (i) ) N so i=1 and the overall error dynamics given by Eq. 15.…”

Section: Lemmamentioning

confidence: 99%

“…15. The networked sub-observers gain matrixK = −X −1 Y (or equivalently K (i) = −X −1 i Y i ) stabilizes the system (7) and minimizes a positive parameter , which represents an upper bound on the H ∞ norm of the transfer matrix from the disturbance D ext to the estimation errorĒ, if there exist a block-…”

Section: Lemmamentioning

confidence: 99%

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Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

Azizi¹,

Khorasani²

2014

Asian Journal of Control

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In this paper, a novel framework for networked estimation of multi-agent systems subject to presence of actuator faults is proposed. This framework is developed based on the notion of sub-observers where within a group of sub-observers each sub-observer estimates certain states that are conditioned on a given input, output, and other state information. We model the overall estimation process by a weighted estimation (WE) digraph. By selecting an appropriate path in the WE digraph, an assigned supervisor can select and configure a set of sub-observers to successfully estimate all the system states. In the presence of large intermittent disturbances, noise, and faults certain sub-observers may become invalid, and consequently the supervisor reconfigures the set of sub-observers by selecting a new path in the estimation digraph such that the impacts of these uncertainties are confined to only the local estimators. This will prevent the propagation of uncertainties on the estimation performance of the entire multi-agent system. Simulation results provided for a five satellite formation flight system in deep space confirm the validity and applicability of our proposed analytical work.

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Section: Fault-augmented State Space Model Of Multi-agent Systemsmentioning

confidence: 99%

Section: Sub-observer Design Proceduresmentioning

confidence: 99%

Section: Sub-observer Design Proceduresmentioning

confidence: 99%

“…Consider the proposed networked subobservers that are governed by the dynamics (7) with the overall gain matrixK = diag(K (i) ) N so i=1 and the overall error dynamics given by Eq. 15.…”

Section: Lemmamentioning

confidence: 99%

Section: Lemmamentioning

confidence: 99%

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Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

Azizi¹,

Khorasani²

2014

Asian Journal of Control

Self Cite

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An Overview of Cooperative and Consensus Control of Multiagent Systems

Davoodi

Gallehdari

Saboori

et al. 2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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There has been a growing interest toward the development of networked unmanned autonomous systems that can operate without an extensive involvement of humans. The motivation for this focus can be traced to the emergence of applications where direct human intervention is not possible due to the environmental hazards, complexity of the tasks, or other restrictions. These networks can consist of a large number of dynamical systems (agents), such as unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned underwater vehicles (UUVs). These systems commonly include a number of sensors, actuators, and decisionmakers. Therefore, the network of these systems is a network of a large number of sensors and actuators or, as is known in the literature, a system of systems (SoS). In this work, we provide a brief overview of controlling these networks, their applications, and the solutions that are proposed for these problems in the literature. Specifically, this article overviews recent results and progress made on multiagent consensus by focusing on cooperative control and consensus (formation) control in the presence of communication, control implementation, and saturation constraints. In addition, we review the active areas of event‐triggered consensus control, network security and attacks on the agents, and networks and resilient consensus control strategies that are proposed to handle these challenges.

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