Fault tolerant approaches based on evolvable hardware and using reconfigurable electronic devices
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evolvable hardware reconfigurable hardware genetic↗
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Results for “Genetic algorithm”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Evolutionary mechanisms for smart on-board adaptive sensing applied to the MECA electrometer
In this paper we describe the initial development of efficient mechanisms for smart on-board adaptive sensing, adaptively controlling the reconfigurable pre-processing analog electronics using evolvable hardware, which will lead to higher quality, lean data.
evolvable hardware reconfigurable hardware genetic↗
Simulator Development for Nanoelectronic Devices
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simulation nanoelectronics resonant tunneling diod↗
Designing Dielectric Grating Filters with PGAPACK
The chapter is concerned with the design of planar dielectric layer diffraction gratings, which exhibit sharp resonances due to the coupling of exterior evanescent diffractive fields to the leaky modes of dielectric waveguides.
genetic algorithms↗
Evolution of CMOS Circuits in Simulations and Directly in Hardware on a Programmable Chip
The paper introduces an approach to automated synthesis of CMOS circuits, based on evolution on a Programmable Transistor Array (PTA).
evolvable hardware reconfigurable hardware genetic↗
Nanoelectronic Modeling at JPL
The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of measurement, analytical and communication systems.
Nanoelectronic Modeling RTD Genetic Algorithm NEMO↗
Optimal adaptive performance and delocalization in NK landscapes
We investigate the evolutionary dynamics of a finite population of sequences adapting to NK fitness landscapes.
simulation evolution adaptaion genetic algorithms↗
Evolutionary computing for the design search and optimization of space vehicle power subsystems
Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.
evolutionary computing genetic algorithms optimiza↗
Evolutionary computing for the design search and optimization of space vehicle power subsystems
Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.
power↗
Hardware platforms for MEMS gyroscope tuning based on evolutionary computation using open-loop and closed -loop frequency response
We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation. We also report on the development of a hardware platform for integrated tuning and closed loop operation of MEMS gyroscopes. The control of this device is implemented through a digital design on a Field Programmable Gate Array (FPGA). The hardware platform easily transitions to an embedded solution that allows for the miniaturization of the system to a single chip.
evolvable hardware↗
Evolutionary Computation Applied to the Tuning of MEMS Gyroscopes
We propose a tuning method for MEMS gyroscopes based on evolutionary computation to efficiently increase the sensitivity of MEMS gyroscopes through tuning and, furthermore, to find the optimally tuned configuration for this state of increased sensitivity. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation.
evolvable hardware↗
Growth Control and Disease Mechanisms in Computational Embryogeny
This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.
Genetic algorithm↗
Swarmie User Manual: A Rover Used for Multi-agent Swarm Research
The ability to create multiple functional yet cost effective robots is crucial for conducting swarming robotics research. The Center Innovation Fund (CIF) swarming robotics project is a collaboration among the KSC Granular Mechanics and Regolith Operations (GMRO) group, the University of New Mexico Biological Computation Lab, and the NASA Ames Intelligent Robotics Group (IRG) that uses rovers, dubbed "Swarmies", as test platforms for genetic search algorithms. This fall, I assisted in the development of the software modules used on the Swarmies and created this guide to provide thorough instructions on how to configure your workspace to operate a Swarmie both in simulation and out in the field.
Robotics↗
Extension of an Object-Oriented Optimization Tool: User's Reference Manual
The National Aeronautics and Space Administration Armstrong Flight Research Center has developed a cost-effective and flexible object-oriented optimization (O (sup 3)) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. This object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the O (sup 3) tool and the discipline modules, or both. Six different sample mathematical problems are presented to demonstrate the performance of the O (sup 3) tool. Instructions for preparing input data for the O (sup 3) tool are detailed in this user's manual.
Multidisciplinary design optimization↗
Results on the Fitness and Population Based Fault Tolerance Approaches using Reconfigurable Electronic Devices
The paper presents and compares two approaches to design fault-tolerant evolvable hardware: one based on the fitness definition and the other based on the population statistics.
evolvable↗
An Evolvable Multi-Agent Approach to Space Operations Engineering
A complex system of spacecraft and ground tracking stations, as well as a constellation of satellites or spacecraft, has to be able to reliably withstand sudden environment changes, resource fluctuations, dynamic resource configuration, limited communication bandwidth, etc., while maintaining the consistency of the system as a whole.
Intelligent↗
Evolutionary Experiments with a Fine-Grained Reconfigurable Architecture for Analog and Digital CMOS Circuits
The paper describes the architectual details of a fine-grained Programmable Transistor Array (PTA) architecture and illustrates its use in evolutionary experiments on the synthesis of both analog and digital circuits.
evolvable↗