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Engineering Commons™

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Selected Works

Electrical and Computer Engineering

Diagnosis

2012

Articles 1 - 3 of 3

Full-Text Articles in Engineering

Software And System Health Management For Autonomous Robotics Missions, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel Sep 2012

Software And System Health Management For Autonomous Robotics Missions, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel

Ole J Mengshoel

Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple sensors, and a mission-critical software system. This software system consists of an operating system, device drivers, controllers, and executives; recently highly complex AI-based autonomy software have also been introduced. Prior to launch, this software has to undergo rigorous verification and validation (V&V). Nevertheless, dormant software bugs, failing sensors, unexpected hardware-software interactions, and unanticipated environmental conditions—likely on a space exploration mission—can cause major software faults that can endanger the entire mission.

Our Integrated Software Health Management (ISWHM) system continuously monitors the hardware sensors and the software …

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Reactive Bayesian Network Computation Using Feedback Control: An Empirical Study, Ole J. Mengshoel, Abe Ishihara, Erik Reed Aug 2012

Reactive Bayesian Network Computation Using Feedback Control: An Empirical Study, Ole J. Mengshoel, Abe Ishihara, Erik Reed

Ole J Mengshoel

This paper investigates the challenge of integrating intelligent systems into varying computational platforms and application mixes while providing reactive (or soft real-time) response. We integrate Bayesian network computation with feedback control, thereby achieving our reactive objective. As a case study we investigate fault diagnosis using Bayesian networks. While we consider the likelihood weighting and junction tree propagation Bayesian network inference algorithms in some detail, we hypothesize that the techniques developed can be broadly applied to achieve reactive intelligent systems. In the empirical study of this paper we demonstrate reactive fault diagnosis for an electrical power system.

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Adaptive Control Of Bayesian Network Computation, Erik Reed, Abe Ishihara, Ole J. Mengshoel Jul 2012

Adaptive Control Of Bayesian Network Computation, Erik Reed, Abe Ishihara, Ole J. Mengshoel

Ole J Mengshoel

This paper considers the problem of providing, for computational processes, soft real-time (or reactive) response without the use of a hard real-time operating system. In particular, we focus on the problem of reactively computing fault diagnosis by means of different Bayesian network inference algorithms on non-real-time operating systems where low-criticality (background) process activity and system load is unpredictable.
To address this problem, we take in this paper a reconfigurable adaptive control approach. Computation time is modeled using an ARX model where the input consists of the maximum number of background processes allowed to run at any given time. To ensure …

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