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At least 19 records

Method and system for environmentally adaptive fault tolerant computing

A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.

Copenhaver, Jason L.↗

Adaptive Fault Tolerance for Many-Core Based Space-Borne Computing

This paper describes an approach to providing software fault tolerance for future deep-space robotic NASA missions, which will require a high degree of autonomy supported by an enhanced on-board computational capability. Such systems have become possible as a result of the emerging many-core technology, which is expected to offer 1024-core chips by 2015. We discuss the challenges and opportunities of this new technology, focusing on introspection-based adaptive fault tolerance that takes into account the specific requirements of applications, guided by a fault model. Introspection supports runtime monitoring of the program execution with the goal of identifying, locating, and analyzing errors. Fault tolerance assertions for the introspection system can be provided by the user, domain-specific knowledge, or via the results of static or dynamic program analysis. This work is part of an on-going project at the Jet Propulsion Laboratory in Pasadena, California.

fault tolerance↗

Fault-tolerant adaptive control for load-following in static space nuclear power systems

The possible use of a dual-loop model-based adaptive control system for load following in static space nuclear power systems is investigated. The proposed approach has thus far been applied only to a thermoelectric space nuclear power system but is equally applicable to other static space nuclear power systems such as thermionic systems.

Parlos, Alexander G.↗

Adaptive fault-tolerant routing in hypercube multicomputers

A connected hypercube with faulty links and/or nodes is called an injured hypercube. To enable any non-faulty node to communicate with any other non-faulty node, information on component failures has to be made available to non-faulty nodes so as to route messages around the faulty components. A distributed adaptive fault tolerant routing scheme is proposed in which each node is required to know only the condition of its own links. This scheme is shown to be capable of routing messages successfully as long as the number of faulty components is less than n (the dimension of the hypercube), and to route messages via shortest paths with a rather high probability. A second routing scheme based on depth-first search is proposed which works in the presence of an arbitrary number of faulty components; however, the paths chosen by this may not always be the shortest. To guarantee shortest paths, every mode must be given information beyond that on its own links; the additional information to be kept at each node for shortest-path routing is determined. Several examples are given to illustrate the results.

Chen, Ming-Syan↗

Adaptive fault-tolerant routing in hypercube multicomputers

A connected hypercube with faulty links and/or nodes is called an injured hypercube. To enable any non-faulty node to communicate with any other non-faulty node in an injured hypercube, the information on component failures has to be made available to non-faulty nodes so as to route messages around the faulty components. A distributed adaptive fault tolerant routing scheme is proposed for an injured hypercube in which each node is required to know only the condition of its own links. Despite its simplicity, this scheme is shown to be capable of routing messages successfully in an injured hypercube as long as the number of faulty components is less than n. Moreover, it is proved that this scheme routes messages via shortest paths with a rather high probabiltiy and the expected length of a resulting path is very close to that of a shortest path. Since the assumption that the number of faulty components is less than n in an n-dimensional hypercube might limit the usefulness of the above scheme, a routing scheme is introduced based on depth-first search which works in the presence of an arbitrary number of faulty components. Due to the insufficient information on faulty components, the paths chosen by the above scheme may not always be the shortest. To guarantee that all messages be routed via shortest paths, it is proposed that every mode be equipped with more information than that on its own links. The effects of this additional information on routing efficiency are analyzed, and the additional information to be kept at each node for the shortest path routing is determined. Several examples and remarks are also given to illustrate the results.

Chen, Ming-Syan↗

Controls and Health Management Technologies for Intelligent Aerospace Propulsion Systems

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Technology Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of an Intelligent Engine. The key enabling technologies for an Intelligent Engine are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Technology Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Garg, Sanjay↗

NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. Also the propulsion systems required to enable the NASA (National Aeronautics and Space Administration) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch at NASA Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Source record↗

Introduction to Advanced Engine Control Concepts

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This presentation describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Sanjay, Garg↗

A Decentralized Adaptive Approach to Fault Tolerant Flight Control

This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

Wu, N. Eva↗

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗

Flight Test Comparison of Different Adaptive Augmentations for Fault Tolerant Control Laws for a Modified F-15 Aircraft

This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.

Burken, John J.↗

Fault-Tolerant Flight Computer

In design concept for adaptive, fault-tolerant flight computer, upon detection of fault in either processor, surviving processor assumes responsibility for both equipment systems. Possible because of cross-strapping between processors, memories, and input/output units. Concept also applicable to other computing systems required to tolerate faults and in which partial loss of processing speed or functionality acceptable price to pay for continued operation in event of faults.

Chau, Savio↗

Model Predictive Fault-Tolerant Tracking Control for PDF Control Systems With Packet Losses

In this article, a fault-tolerant tracking control strategy is investigated for nonlinear probability density function (PDF) control systems with the actuator fault, uncertainties, unknown disturbance, and random packet losses. The control input signal dropout and measurement signal dropouts are described as the independent Bernoulli distribution. An adaptive fault diagnosis (FD) observer based on the Lyapunov function is given to simultaneously estimate the fault, disturbance, and state with packet losses. Furthermore, different from the traditional robust fault-tolerant control (FTC), a new active fault-tolerant tracking controller is designed based on the model predictive control framework, which has better adaptive fault-tolerant performance. Finally, the validity of the proposed FTC method has been proved by a simulation study of a papermaking process.

42 ENGINEERING↗

Feedback-Based Fault-Tolerant and Health-Adaptive Optimal Charging of Batteries

The key technology barriers that hinder the growth of Electric Vehicles (EVs) are long charging time, the shorter life-time of EV batteries, and battery safety. Specifically, EV charging protocols have significant effects on battery lifetime and safety. If not charged properly, the battery could end up with shorter life, and more importantly, improper charging can cause battery faults leading to catastrophic failures. To overcome these barriers, we propose a closed-loop feedback based approach, that enables real-time optimal fast charging protocol adaptation to battery health and possess active diagnostic capabilities in the sense that, during charging, it detects real-time faults and takes corrective action to mitigate such fault effects. We utilize battery electrical-thermal model, explicit battery capacity and power fade aging models, and thermal fault model to capture battery behavior. In conjunction with the models, we adopt linear quadratic optimal control techniques to realize the feedback-based control algorithm. Simulation studies are presented to illustrate the effectiveness of the proposed scheme.

batteries↗

An Analysis of Failure Handling in Chameleon, A Framework for Supporting Cost-Effective Fault Tolerant Services

The desire for low-cost reliable computing is increasing. Most current fault tolerant computing solutions are not very flexible, i.e., they cannot adapt to reliability requirements of newly emerging applications in business, commerce, and manufacturing. It is important that users have a flexible, reliable platform to support both critical and noncritical applications. Chameleon, under development at the Center for Reliable and High-Performance Computing at the University of Illinois, is a software framework. for supporting cost-effective adaptable networked fault tolerant service. This thesis details a simulation of fault injection, detection, and recovery in Chameleon. The simulation was written in C++ using the DEPEND simulation library. The results obtained from the simulation included the amount of overhead incurred by the fault detection and recovery mechanisms supported by Chameleon. In addition, information about fault scenarios from which Chameleon cannot recover was gained. The results of the simulation showed that both critical and noncritical applications can be executed in the Chameleon environment with a fairly small amount of overhead. No single point of failure from which Chameleon could not recover was found. Chameleon was also found to be capable of recovering from several multiple failure scenarios.

Haakensen, Erik Edward↗

Data systems - Optical bus will connect distributed system

The fiber optics buses currently under consideration for the NASA space station program will have data rates of at least 20 Mb/sec. The network interconnection scheme that will eventually be used is, however, uncertain. A NASA-Langley effort on graph networks includes adaptive, fault-tolerant and self-correcting operations. A breadboard program at NASA-Johnson includes evaluations of standard devices, called 'bus interface units', in an adaptive and fault-correcting chordal or concentric ring type of network. Fiber optics would allow an evolution to wavelength modulation techniques in such systems.

Swingle, W. L.↗

Efficient Client Selection in Federated Learning

Federated Learning (FL) enables decentralized machine learning while preserving data privacy. This paper proposes a novel client selection framework that integrates differential privacy and fault tolerance. The adaptive client selection adjusts the number of clients based on performance and system constraints, with noise added to protect privacy. Evaluated on the UNSW-NB15 and ROAD datasets for network anomaly detection, the method improves accuracy by 7% and reduces training time by 25 % compared to baselines. Fault tolerance enhances robustness with minimal performance trade-offs.

Marfo, William [University of Texas at El Paso,Dep↗

Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case

Federated Learning (FL) has become a ubiquitous approach for training machine learning models on decentralized data, addressing the myriad privacy concerns inherent in traditional centralized methods. However, the efficiency of FL depends on effective client selection and robust privacy preservation mechanisms. Inadequate client selection may lead to suboptimal model performance, while insufficient privacy measures risk exposing sensitive data. This paper proposes a client selection framework for FL that integrates differential privacy and fault tolerance. Our adaptive approach dynamically adjusts the number of selected clients based on model performance and system constraints, ensuring privacy through calibrated noise addition. We evaluate our method on a network anomaly detection use case using the UNSW-NB15 and ROAD datasets. Results show up to a 7% increase in accuracy and a 25% reduction in training time compared to FedL2P. Moreover, we highlight the trade-offs between privacy budgets and model performance, with higher privacy budgets reducing noise and improving accuracy. Our fault tolerance mechanism, while causing a slight performance drop, enhances robustness to client failures. Statistical validation using Mann-Whitney U tests confirms the significance of these improvements (p < 0.05).

Marfo, William [University of Texas at El Paso,Dep↗