Search NASA⌕ Search

SEARCH · Search NASA

Results for “Adaptive tuning”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Understanding and Evaluating Assurance Cases

Assurance cases are a method for providing assurance for a system by giving an argument to justify a claim about the system, based on evidence about its design, development, and tested behavior. In comparison with assurance based on guidelines or standards (which essentially specify only the evidence to be produced), the chief novelty in assurance cases is provision of an explicit argument. In principle, this can allow assurance cases to be more finely tuned to the specific circumstances of the system, and more agile than guidelines in adapting to new techniques and applications. The first part of this report (Sections 1-4) provides an introduction to assurance cases. Although this material should be accessible to all those with an interest in these topics, the examples focus on software for airborne systems, traditionally assured using the DO-178C guidelines and its predecessors. A brief survey of some existing assurance cases is provided in Section 5. The second part (Section 6) considers the criteria, methods, and tools that may be used to evaluate whether an assurance case provides sufficient confidence that a particular system or service is fit for its intended use. An assurance case cannot provide unequivocal "proof" for its claim, so much of the discussion focuses on the interpretation of such less-than-definitive arguments, and on methods to counteract confirmation bias and other fallibilities in human reasoning.

Rushby, John↗

Object and Gas Source Detection with Robotic Platforms in Perceptually-Degraded Environments

In exploration-oriented robotic missions for disaster relief in unknown subterranean environments, it is of prime importance for a human supervisor to rapidly gain situational awareness of salient objects within the environment. In this paper we present an automated object detection pipeline that is adaptable to heterogeneous robots with arbitrary sensor configurations. It has been deployed in time-critical scenarios with multiple collaborative robots in a variety of demanding underground environments. For visually observable objects, detections are made in both the visible and thermal spectra using a state-of-the-art machine learning framework for object detection and classification. Our pipeline can be rapidly adapted to a specific task by using a small, structured dataset to fine-tune a pre-trained convolutional neural network (CNN). Relative localization is separated from the CNN for speed of operation. A robust architecture for localization is used with outlier rejection and a hierarchy of fall-back distance measurement methods. Point-source objects such as gas and WiFi hotspots can also be detected, by tracking signal strength over time and presenting an intuitive visualization on a map. Observations of each object types are presented to the operator in ranked confidence order for final evaluation.

Agha-mohammadi, Ali-akbar↗

Implementation and Evaluation of Multiple Adaptive Control Technologies for a Generic Transport Aircraft Simulation

Presented here is the evaluation of multiple adaptive control technologies for a generic transport aircraft simulation. For this study, seven model reference adaptive control (MRAC) based technologies were considered. Each technology was integrated into an identical dynamic-inversion control architecture and tuned using a methodology based on metrics and specific design requirements. Simulation tests were then performed to evaluate each technology s sensitivity to time-delay, flight condition, model uncertainty, and artificially induced cross-coupling. The resulting robustness and performance characteristics were used to identify potential strengths, weaknesses, and integration challenges of the individual adaptive control technologies

Campbell, Stefan F.↗

Adaptive noncolocated velocity feedback for vibration damping

A method is proposed for adaptive noncolocated velocity feedback control of flexible structure vibrations. The approach, denoted as auto-tuning, is to drive the system into a sequence of controlled oscillations to provide accurate knowledge of the plant characteristics in the vicinity of the phase cross-over frequencies. An allpass phase notch filter cascade is used as the control architecture to phase stabilize each destabilizing mode in the plant transfer function. The allpass phase notch filter cascade is tuned precisely by the information extracted from the controlled oscillations.

Bayard, David S.↗

The Peak Absorbance Wavelength of Photosynthetic Pigments Around Other Stars From Spectral Optimization

In the search for life on other planets, the presence of photosynthetic surface vegetation may be detectable from the colors of light it reflects, which on the modern Earth is a steep increase in reflectance between the red and near-infrared wavelengths, a “red edge.” This edge-like signature occurs at wavelengths of peak photon absorbance, which are the result of adaptations of the phototroph to their spectral environment. On planets orbiting different stellar types, red edge analogs may occur at other colors than red. Thus, knowing the wavelengths at which photosynthetic organisms preferentially absorb and reflect photons is necessary to detect red edge analogs on other planets. Using a numerical model that predicts the absorbance spectrum of extant photosynthetic pigments on Earth from Marosvolgyi & van Gorkom (2010), we calculate the absorbance spectrum for pigments on an Earth-like planet around F through late M type stars that are adapted for maximal energy production. In this model, cellular energy production is maximized when pigments are tuned to absorb at the wavelength that maximizes energy input from incident photons while minimizing energy losses due to thermal emission and building cellular photosynthetic apparatus. We find that peak photon absorption for photosynthetic organisms around F type stars tends to be in the blue while for G, K, and early M type stars, red or just beyond is preferred. Around the coolest M type stars, these organisms may preferentially absorb in the near-infrared, possibly past 1 micron. These predictions are consistent with previous, qualitative estimates of pigment absorptance. Our predicted absorbance spectra for photosynthetic surface organisms depend on both the stellar type and planetary atmospheric composition, especially atmospheric water vapor concentrations, which alter the availability of surface photons and thus the predicted pigment absorption. By constraining the absorbance spectra of alien, photosynthetic organisms, future observations may be better equipped to detect the weak spectral signal of red edge analogs.

astrobiology↗

Adaptive Control of Small Outboard-Powered Boats for Survey Applications

Four autopilot controllers have been developed in this work that can both hold a desired heading and follow a straight line. These PID, adaptive PID, neuro-adaptive, and adaptive augmenting control algorithms have all been implemented into a numerical simulation of a 33-foot center console vessel with wind, waves, and current disturbances acting in the perpendicular (across-track) direction of the boat s desired trajectory. Each controller is tested for its ability to follow a desired heading in the presence of these disturbances and then to follow a straight line at two different throttle settings for the same disturbances. These controllers were tuned for an input thrust of 2000 N and all four controllers showed good performance with none of the controllers significantly outperforming the others when holding a constant heading and following a straight line at this engine thrust. Each controller was then tested for a reduced engine thrust of 1200 N per engine where each of the three adaptive controllers reduced heading error and across-track error by approximately 50% after a 300 second tuning period when compared to the fixed gain PID, showing that significant robustness to changes in throttle setting was gained by using an adaptive algorithm.

VanZwieten, T.S.↗

An Ad-Hoc Adaptive Pilot Model for Pitch Axis Gross Acquisition Tasks

An ad-hoc algorithm is presented for real-time adaptation of the well-known crossover pilot model and applied to pitch axis gross acquisition tasks in a generic fighter aircraft. Off-line tuning of the crossover model to human pilot data gathered in a fixed-based high fidelity simulation is first accomplished for a series of changes in aircraft dynamics to provide expected values for model parameters. It is shown that in most cases, for this application, the traditional crossover model can be reduced to a gain and a time delay. The ad-hoc adaptive pilot gain algorithm is shown to have desirable convergence properties for most types of changes in aircraft dynamics.

Hanson, Curtis E.↗

Mechanically Tunable Radiative Cooling for Adaptive Thermal Control

Passive radiative cooling is currently thefrontier technology in renewable-energy research. Interms of extraterrestrial applications, radiative cooling is a critical component to the thermalmanagement system of a spacecraft, where the extreme environment of space can cause largetemperature variations that can break and damage equipment. For terrestrial applications,nocturnal or daytime radiative cooling is expected to lead to cost-effective passive heatmanagement without the need of inefficient and costly artificial refrigeration technologies.However, most currently available radiative cooling systems cannot be changed dynamically andradiate a constant static amount of thermal power. Dynamically tunable adaptive radiativecooling systems will be a critical development to prolong the lifetime of spacecraft or improvethe efficiency of terrestrial cooling systems. Here we propose stretchable radiative coolingdesigns that can be substantially tuned by using the simple physical mechanism of mechanical strain. When their structure is stretched, the radiated power is significantly reduced. We developa modeling method that can simulate mechanical stretching combined with electromagnetic response to compute the tunable thermal emission of these new adaptive radiative coolingsystems. The presented photonically engineered structures can be used as coatings to achieveefficient adaptive thermal control of various objects in a cost-effective and environmentallyfriendly way. The proposed designs are much simpler to be realized than others found in theliterature and the best design achieves a high thermal emission power with a tunable range on theorder of 132 W/m2.

Andrew Butler↗

A neural fuzzy controller learning by fuzzy error propagation

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Nauck, Detlef↗

Hybrid state-space self-tuning control of uncertain linear systems

The paper presents a hybrid state-space self-tuner using a new dual-rate sampling scheme for digital adaptive control of continuous-time uncertain linear systems. A state-space-based recursive least-squares algorithm, together with a variable forgetting factor, is used for direct estimations of both the equivalent discrete-time uncertain linear system parameters and the associated discrete-time state of a continuous-time uncertain linear system from the sampled input and output data. An analogue optimal regional pole-placement design method is used for designing an optimal observer-based analogue controller. A suboptimal observer-based digital controller is then designed from the designed analogue controller using digital redesign technique. To enhance the robustness of parameter identification and state estimation algorithms, a dynamic bound for a class of uncertain bilinear parameters and a fast-rate digital controller are developed at each fast-sampling period. Also, to accommodate computation loads and computation delay for developing the advanced hybrid self-tuner, the designed analogue controller and observer gains are both updated at each slow-sampling period. This control technique has been successfully applied to benchmark control problems.

Shieh, L. S.↗

Algorithms and data structures for adaptive multigrid elliptic solvers

Adaptive refinement and the complicated data structures required to support it are discussed. These data structures must be carefully tuned, especially in three dimensions where the time and storage requirements of algorithms are crucial. Another major issue is grid generation. The options available seem to be curvilinear fitted grids, constructed on iterative graphics systems, and unfitted Cartesian grids, which can be constructed automatically. On several grounds, including storage requirements, the second option seems preferrable for the well behaved scalar elliptic problems considered here. A variety of techniques for treatment of boundary conditions on such grids are reviewed. A new approach, which may overcome some of the difficulties encountered with previous approaches, is also presented.

Vanrosendale, J.↗

TPSAS-NF1676L-32467-DND

With the launch of a new generation of Geostationary satellites (GEO) such as Himawari and GOES-16 & 17, cloud detection using satellite imager data has been greatly enhanced with increased spectral bands, and higher temporal and spatial resolutions. A concern for all geostationary sensors, however, are changes in instrument sensitivity and algorithm performance at different viewing for daytime and nighttime. CALIPSO lidar observations provide a valuable reference for assessing these impacts as the satellite flies in a sun-synchronous orbit and crosses a wide range of GEO viewing angles each day. This paper will present the cloud mask results using the imager data from Himawari (AHI) and GOES-16&17 (ABI). The detection algorithms have been adapted from the Cloud and Earth’s Radiant Energy System (CERES) MODIS Edition 4 cloud mask, and adjusted and tuned to geo-satellites. They are used operationally for the CERES Time and Space Averaging (TISA) gridded cloud products and for near-real-time retrievals for weather and nowcasting applications.

Qing Z. Trepte↗

Compact Two-step Laser Time-of-Flight Mass Spectrometer for in Situ Analyses of Aromatic Organics on Planetary Missions

RATIONALE A miniature time-of-flight mass spectrometer has been adapted to demonstrate two-step laser desorption-ionization (LOI) in a compact instrument package for enhanced organics detection. Two-step LDI decouples the desorption and ionization processes, relative to traditional laser ionization-desorption, in order to produce low-fragmentation conditions for complex organic analytes. Tuning UV ionization laser energy allowed control ofthe degree of fragmentation, which may enable better identification of constituent species. METHODS A reflectron time-of-flight mass spectrometer prototype measuring 20 cm in length was adapted to a two-laser configuration, with IR (1064 nm) desorption followed by UV (266 nm) postionization. A relatively low ion extraction voltage of 5 kV was applied at the sample inlet. Instrument capabilities and performance were demonstrated with analysis of a model polycyclic aromatic hydrocarbon, representing a class of compounds important to the fields of Earth and planetary science. RESULTS L2MS analysis of a model PAH standard, pyrene, has been demonstrated, including parent mass identification and the onset o(tunable fragmentation as a function of ionizing laser energy. Mass resolution m/llm = 380 at full width at half-maximum was achieved which is notable for gas-phase ionization of desorbed neutrals in a highly-compact mass analyzer. CONCLUSIONS Achieving two-step laser mass spectrometry (L2MS) in a highly-miniature instrument enables a powerful approach to the detection and characterization of aromatic organics in remote terrestrial and planetary applications. Tunable detection of parent and fragment ions with high mass resolution, diagnostic of molecular structure, is possible on such a compact L2MS instrument. Selectivity of L2MS against low-mass inorganic salt interferences is a key advantage when working with unprocessed, natural samples, and a mechanism for the observed selectivity is presented.

Getty, Stephanie↗

Some adaptive filtering techniques applied to the passive remote sensing problem

A review is made of recursive statistical regression techniques incorporating past or past and future observations through smoothing and Kalman filtering, respectively; with results for the cases of the Tiros-N/MSU and Nimbus-6/Scams remote sensing satellite experiments. In response to the lack of a satisfactory model for the medium sounded, which is presently a major limitation on retrieval technique performance, a novel, global approach is proposed which casts the retrieval problem into the framework of adaptive filtering. A numerical implementation of such an adaptive system is presented, with a multilayer, semi-spectral general circulation model for the atmosphere being used to fine-tune the sensor as well as the dynamical equations of a Kalman filter. It is shown that the assimilation of radiometric data becomes a straightforward subproblem.

Toldalagi, P. M.↗

ATM photoheliograph

The design and fabrication are presented of a 65 cm photoheliograph functional verification unit (FVU) installed in a major solar observatory. The telescope is used in a daily program of solar observation while serving as a test bed for the development of instrumentation to be included in early space shuttle launched solar telescopes. The 65 cm FVU was designed to be mechanically compatible with the ATM spar/canister and would be adaptable to a second ATM flight utilizing the existing spar/canister configuration. An image motion compensation breadboard and a space-hardened, remotely tuned H alpha filter, as well as solar telescopes of different optical configurations or increased aperture are discussed.

Prout, R. A.↗

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or create more accurate transcripts of air traffic management conversations. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement (LOA) which is used as the evaluation case in this paper. These applications can benefit from the use of state-of-the-art Natural Language Processing (NLP) techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of transferring pre-trained large language models to the aviation domain by adapting transformer based models using aviation datasets. This paper utilized two datasets to adapt a ‘Robustly Optimized Bidirectional Encoder Representations from Transformers Approach’ (RoBERTa) model and two down-stream classification tasks to assess its performance. These datasets are all built upon Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. The first two datasets are used for the adaptation of RoBERTa to the aviation domain and were of different sizes to assess the number of documents needed to adapt to the aviation domain. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the unsupervised adaptation. The second dataset is a separate set of LOA documents with two sets of classification labels to be used for evaluation; one at the document level and one at the line level. These down-stream evaluations allowed the measurement of improvement by adapting RoBERTa. The accuracy increased by 4-6% on both tasks and the F1 score on the class of interest increased by 4-8% from the adaptation.

Air Traffic Management↗

Testing and Development of a Percussive Augmenter for Rotary Drills

Hammering drills are effective in fracturing the drilled medium while rotary drills remove cuttings. The combination provides a highly effective penetration mechanism. Piezoelectric actuators were integrated into an adapter to produce ultrasonic percussion; augmenting rotary drilling. The drill is capable of operating at low power, low applied force and, with proper tuning, low noise. These characteristics are of great interest for future NASA missions and the construction/remodeling industry. The developed augmenter connects a commercially available drill and bit and was tested to demonstrate its capability. Input power to the drill was read using a multimeter and the augmenter received a separate input voltage. The drive frequency of the piezoelectric actuator was controlled by a hill climb algorithm that optimizes and records average power usage to operate the drill at resonating frequency. Testing the rotary drill and augmenter across a range of combinations with total power constant at 160 Watts has shown results in concrete and limestone samples that are as good as or better than the commercial drill. The drill rate was increased 1.5 to over 10 times when compared to rotation alone.

rotary-hammering↗

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or create more accurate transcripts of air traffic management conversations. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement (LOA) which is used as the evaluation case in this paper. These applications can benefit from the use of state-of-the-art Natural Language Processing (NLP) techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of transferring pre-trained large language models to the aviation domain by adapting transformer based models using aviation datasets. This paper utilized two datasets to adapt a ‘Robustly Optimized Bidirectional Encoder Representations from Transformers Approach’ (RoBERTa) model and two down-stream classification tasks to assess its performance. These datasets are all built upon Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. The first two datasets are used for the adaptation of RoBERTa to the aviation domain and were of different sizes to assess the number of documents needed to adapt to the aviation domain. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the unsupervised adaptation. The second dataset is a separate set of LOA documents with two sets of classification labels to be used for evaluation; one at the document level and one at the line level. These down-stream evaluations allowed the measurement of improvement by adapting RoBERTa. The accuracy increased by 4-6% on both tasks and the F1 score on the class of interest increased by 4-8% from the adaptation.

Air Traffic Management↗