Fault detection of networked control systems with limited communication

Wang, Yongqiang; Ye, Hao; Ding, Steven X.; Cheng, Yue; Zhang, Ping; Wang, Guizeng

doi:10.1080/00207170802558967

Cited by 29 publications

(12 citation statements)

References 23 publications

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“…, e T N ] T . From (16), (19) and (30), it iṡ V =−2k oỹ ⋆TL ⋆ỹ ⋆ − 2k oỹ ⋆T Π ⋆ η ⋆ + 2ỹ ⋆Tφ ⋆ +2e T −(I N ⊗ K)e +φ + (I N ⊗ K)η…”

Section: A Proof Of Theoremmentioning

confidence: 99%

“…Gains k o , k c , K, G in (6), (13), (16), (17) were set to k o = 5, k c = 3, K = 2I 2 , G = 0.05I 2 , respectively. The measurement noise η i in (3) is assumed to be a normally distributed random vector with null mean, uncorrelated components and standard deviation of 0.01 m. The network topology is assumed to be circular.…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…To the purpose, each robot is required to be able to recognize the presence of a faulty robot in the team (fault detection), to identify the robot in fault (fault isolation), and to compensate the fault or to exclude the faulty robot from the team rearranging the mission (fault recovery). Fault detection, isolation and reconfiguration problems have been widely addressed in the past years for the case of single unit systems [8] as well as for the case of not distributed multi-robot systems [16], [12]. The FDI problem for distributed systems, indeed, only recently has attracted the research community.…”

Section: Introductionmentioning

confidence: 99%

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Distributed fault detection and recovery for networked robots

Arrichiello

Marino

Pierri

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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The paper deals with the problem of decentralized fault detection, isolation and recovery for teams of networked robots. The proposed strategy is a combination of distributed and local approaches that allow the robots to deal with both recoverable and unrecoverable faults. A local adaptive fault observer is used to locally compensate recoverable faults, while a distributed fault detection and isolation strategy is used to allow each robot to detect unrecoverable faults on other teammates even if not directly connected; once the faulty robots have been isolated, they are removed from the team and the mission is rearranged. Results of numerical simulations and experiments involving a team of 5 mobile robots are provided to show the effectiveness of the approach

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“…, e T N ] T . From (16), (19) and (30), it iṡ V =−2k oỹ ⋆TL ⋆ỹ ⋆ − 2k oỹ ⋆T Π ⋆ η ⋆ + 2ỹ ⋆Tφ ⋆ +2e T −(I N ⊗ K)e +φ + (I N ⊗ K)η…”

Section: A Proof Of Theoremmentioning

confidence: 99%

Section: Numerical Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed fault detection and recovery for networked robots

Arrichiello

Marino

Pierri

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…The authors in [22] show that there exists a trade-off between the fault detection rate and the FAR. More recently, the existence of a compromise between the time to detect a fault and the fault sensitivity has been demonstrated in [23]. Nevertheless, none of them explores the compromises between the minimum detectable faults, the FAR and the fault diagnosis (detection and estimation) speed.…”

Section: Introductionmentioning

confidence: 99%

Performance Tradeoffs for Networked Jump Observer-Based Fault Diagnosis

Dolz

Peñarrocha

Sanchis

2015

IEEE Trans. Signal Process.

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Abstract-In this paper, we address the fault diagnosis problem for discrete-time multi-sensor systems over communication networks with measurement dropouts. We use the measurement outcomes to model the measurement reception scenarios. Based on this, we propose the use of a jump observer to diagnose multiple faults. We model the faults as slow time-varying signals and introduce this dynamic in the observer to estimate the faults and to generate a residual. The fault detection is assured by comparing the residual signal with a prescribed threshold. We design the jump observer, the residual and the threshold to attain disturbance attenuation, fault tracking and detection conditions and a given false alarm rate. The false alarm rate is upper bounded by means of Markov's inequality. We explore the tradeoffs between the minimum detectable faults, the false alarm rate and the response time to faults of the fault diagnoser. By imposing the disturbances and measurement noises to be Gaussian, we tighten the false alarm rate bound which improves the time needed to detect a fault. A numerical example is provided to illustrate the effectiveness of the theory developed in the paper.Index Terms-Fault diagnosis, false alarm rate, time to detect faults, jump linear system, dropouts.

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“…Several FDI strategies for single unit systems both in continuous (Zhang et al, 2002) or discrete-time have been proposed in the literature, but only in the last years the fault diagnosis for multi-robot systems has been object of wider attention from the research community. In Wang et al (2009), a centralized approach is presented where a central station, aimed at detecting and isolating faults over the whole system, collects information about actuators and sensors coming from each robot. A comparison between a centralized (with a central unit collecting all the information), semi-decentralized (with information exchange only between neighboring robots), and fully decentralized (in which each robot only knows its own state) FDI approaches is presented in Meskin and Khorasani (2009).…”

Section: Introductionmentioning

confidence: 99%

Distributed Fault-Tolerant Control for Networked Robots in the Presence of Recoverable/Unrecoverable Faults and Reactive Behaviors

2017

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The paper presents an architecture for distributed control of multi-robot systems with an integrated fault detection, isolation, and recovery strategy. The proposed solution is based on a distributed observer-controller schema where each robot, by communicating only with its direct neighbors, is able to estimate the overall state of the system; such an estimate is then used by the controllers of each robot to achieve global missions as, for example, centroid and formation tracking. The information exchanged among the observers is also used to compute residual vectors that allow each robot to detect failures on anyone of the teammates, even if not in direct communication. The proposed strategy considers both recoverable and unrecoverable actuator faults as well as it properly manages the possible activation of reactive local control behaviors of the robots (e.g., the activation of obstacle avoidance strategy), which generate control inputs different from those required by the global mission control. In particular, when the robots are subject to recoverable faults, those are managed at a local level by computing a proper compensating control action. On the other side, when the robots are subject to unrecoverable faults, the faults are isolated from anyone of the teammates by means of a distributed fault detection and isolation strategy; then, the faulty robots are removed from the team and the mission is rearranged. The proposed strategy is validated via numerical simulations where the system properly identifies and manages the different cases of recoverable and unrecoverable actuator faults, as well as it manages the activation of local reactive control in an integrated case study.

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Fault detection of networked control systems with limited communication

Cited by 29 publications

References 23 publications

Distributed fault detection and recovery for networked robots

Distributed fault detection and recovery for networked robots

Performance Tradeoffs for Networked Jump Observer-Based Fault Diagnosis

Distributed Fault-Tolerant Control for Networked Robots in the Presence of Recoverable/Unrecoverable Faults and Reactive Behaviors

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