Fault Diagnosis in Hybrid Systems using Possible Conflicts

Bregón, Aníbal; Alonso, Carlos J.; Biswas, Gautam; Pulido, Belarmino; Moya, Noemi

doi:10.3182/20120829-3-mx-2028.00122

Cited by 15 publications

(14 citation statements)

References 12 publications

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“…Proposition 1: Two modes q i and q j are nondiscernible iff the consistency indicators of the two modes satisfy i (k) = j (k) for any (u(k), y(k)) and any time instant k. Proof: According to Definition 1 two modes q i and q j are nondiscernible iff any couple of signals (u(k), y(k)) that are consistent with mode q i are also consistent with mode q j , and viceversa. Therefore, from the consistency indicator definition (12), it follows that their corresponding consistency indicator vectors i (k) and j (k) are equal.…”

Section: B Discernibilitymentioning

confidence: 99%

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An Incremental Hybrid System Diagnoser Automaton Enhanced by Discernibility Properties

Vento

Travé-Massuyès

Puig

et al. 2015

IEEE Trans. Syst. Man Cybern, Syst.

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This paper proposes a method to track the system mode and diagnose a hybrid system without building an entire diagnoser off-line. The method is supported by a hybrid automaton (HA) model that represents the hybrid system continuous and discrete behavioral dynamics. This model is built on request through parallel composition of the component HA models. Diagnosis is performed by interpreting the events and measurements issued by the physical system directly on the HA model. This interpretation allows us to construct the useful parts of the diagnoser developing only the branches that are required to explain the occurrence of incoming events. The resulting diagnoser adapts to the system operational life and is much less demanding in terms of memory storage than the entire diagnoser. In addition to this feature, the proposed framework subsumes previous works in that it copes with both structural and nonstructural faults. The method is validated by the application to a case study based on the sewer network of the city of Barcelona. Index Terms-Discrete event systems, fault diagnosis, hybrid automaton (HA), hybrid systems, sewer systems. I. INTRODUCTION T HE majority of real systems are controlled on-line and supervised by means of automatic computer-based control systems. The behavior of these systems arises from continuous plant dynamics that can be described by continuous state variables and supervisory control that generates actuator signals at discrete-time points to change regulator set-points or the plant configuration. Diagnosing these systems is a real issue as they are subject to faults that may appear in any of the plant components, in sensors or actuators [15], [27], [29], [30]. These complex systems are modeled using hybrid models that integrate continuous and discrete dynamics. These often take the form of hybrid automaton (HA) models [22] or hybrid bond graph models [16], [27]. Then, this model can support Manuscript

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Section: B Discernibilitymentioning

confidence: 99%

“…the monitoring of the system, fault diagnosis and control tasks. Model-based online diagnosis requires quick and robust reconfiguration processes when a mode change occurs, as well as the ability to keep the nominal behavior of the system on track during transient states [12].…”

mentioning

confidence: 99%

An Incremental Hybrid System Diagnoser Automaton Enhanced by Discernibility Properties

Vento

Travé-Massuyès

Puig

et al. 2015

IEEE Trans. Syst. Man Cybern, Syst.

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“…This is our current research topic right now, extending the current BG-PC approach with Hybrid Bond-Graph Possible Conflicts [4,22,25].…”

Section: Testing In Several Diagnosis Scenariosmentioning

confidence: 99%

“…This work propose to adapt existing solutions for the control of these systems [13], and to couple it with a generic type of traction subsystem [15,18]. The main contribution of this work is to provide a unique modelling framework for both the simulation and diagnosis of these types of systems: the BG models [6,26] and Bond-Graph Possible Conflicts, a simplified version of Hybrid Bond-Graph Possible Conflicts [4,25].…”

Section: Testing In Several Diagnosis Scenariosmentioning

confidence: 99%

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Autonomous vehicle traction subsystem modeling and diagnosis using BG-PCs

Alonso-González¹,

Bregón²,

Pulido³

et al.

Kalpa Publications in Computing

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Fault diagnosis is an essential part in the Health Management of autonomous vehicles. Within these vehicles the traction subsystem is a critical component, especially in those exploring planetary surfaces. Recent advances in brushless DC motors has raised the interest in new models and control configurations to integrate them in those vehicles due to their low energy consumption high torque/-mass ratio and low maintenance requirements. In this work we develop a full Bond Graph model of this subsystem, including the brushless motor and the control blocks needed for proper and efficient operation. These models will allow us to perform fault diagnosis with Bond Graph Possible Conflicts as the unifying formalism. We derive the Bond Graph-Possible Conflicts of the system, discussing the viability of the proposal.

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