Adaptive Wing Camber Optimization: A Periodic Perturbation Approach

NASA Technical Reports Server (NTRS)

Espana, Martin; Gilyard, Glenn

1994-01-01

Available redundancy among aircraft control surfaces allows for effective wing camber modifications. As shown in the past, this fact can be used to improve aircraft performance. To date, however, algorithm developments for in-flight camber optimization have been limited. This paper presents a perturbational approach for cruise optimization through in-flight camber adaptation. The method uses, as a performance index, an indirect measurement of the instantaneous net thrust. As such, the actual performance improvement comes from the integrated effects of airframe and engine. The algorithm, whose design and robustness properties are discussed, is demonstrated on the NASA Dryden B-720 flight simulator.

On-board attitude determination for the Explorer Platform satellite

NASA Technical Reports Server (NTRS)

Jayaraman, C.; Class, B.

1992-01-01

This paper describes the attitude determination algorithm for the Explorer Platform satellite. The algorithm, which is baselined on the Landsat code, is a six-element linear quadratic state estimation processor, in the form of a Kalman filter augmented by an adaptive filter process. Improvements to the original Landsat algorithm were required to meet mission pointing requirements. These consisted of a more efficient sensor processing algorithm and the addition of an adaptive filter which acts as a check on the Kalman filter during satellite slew maneuvers. A 1750A processor will be flown on board the satellite for the first time as a coprocessor (COP) in addition to the NASA Standard Spacecraft Computer. The attitude determination algorithm, which will be resident in the COP's memory, will make full use of its improved processing capabilities to meet mission requirements. Additional benefits were gained by writing the attitude determination code in Ada.

The Results of a Simulator Study to Determine the Effects on Pilot Performance of Two Different Motion Cueing Algorithms and Various Delays, Compensated and Uncompensated

NASA Technical Reports Server (NTRS)

Guo, Li-Wen; Cardullo, Frank M.; Telban, Robert J.; Houck, Jacob A.; Kelly, Lon C.

2003-01-01

A study was conducted employing the Visual Motion Simulator (VMS) at the NASA Langley Research Center, Hampton, Virginia. This study compared two motion cueing algorithms, the NASA adaptive algorithm and a new optimal control based algorithm. Also, the study included the effects of transport delays and the compensation thereof. The delay compensation algorithm employed is one developed by Richard McFarland at NASA Ames Research Center. This paper reports on the analyses of the results of analyzing the experimental data collected from preliminary simulation tests. This series of tests was conducted to evaluate the protocols and the methodology of data analysis in preparation for more comprehensive tests which will be conducted during the spring of 2003. Therefore only three pilots were used. Nevertheless some useful results were obtained. The experimental conditions involved three maneuvers; a straight-in approach with a rotating wind vector, an offset approach with turbulence and gust, and a takeoff with and without an engine failure shortly after liftoff. For each of the maneuvers the two motion conditions were combined with four delay conditions (0, 50, 100 & 200ms), with and without compensation.

Electronic Thermometer Readings

NASA Technical Reports Server (NTRS)

2001-01-01

NASA Stennis' adaptive predictive algorithm for electronic thermometers uses sample readings during the initial rise in temperature and applies an algorithm that accurately and rapidly predicts the steady state temperature. The final steady state temperature of an object can be calculated based on the second-order logarithm of the temperature signals acquired by the sensor and predetermined variables from the sensor characteristics. These variables are calculated during tests of the sensor. Once the variables are determined, relatively little data acquisition and data processing time by the algorithm is required to provide a near-accurate approximation of the final temperature. This reduces the delay in the steady state response time of a temperature sensor. This advanced algorithm can be implemented in existing software or hardware with an erasable programmable read-only memory (EPROM). The capability for easy integration eliminates the expense of developing a whole new system that offers the benefits provided by NASA Stennis' technology.

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Direct adaptive performance optimization of subsonic transports: A periodic perturbation technique

NASA Technical Reports Server (NTRS)

Espana, Martin D.; Gilyard, Glenn

1995-01-01

Aircraft performance can be optimized at the flight condition by using available redundancy among actuators. Effective use of this potential allows improved performance beyond limits imposed by design compromises. Optimization based on nominal models does not result in the best performance of the actual aircraft at the actual flight condition. An adaptive algorithm for optimizing performance parameters, such as speed or fuel flow, in flight based exclusively on flight data is proposed. The algorithm is inherently insensitive to model inaccuracies and measurement noise and biases and can optimize several decision variables at the same time. An adaptive constraint controller integrated into the algorithm regulates the optimization constraints, such as altitude or speed, without requiring and prior knowledge of the autopilot design. The algorithm has a modular structure which allows easy incorporation (or removal) of optimization constraints or decision variables to the optimization problem. An important part of the contribution is the development of analytical tools enabling convergence analysis of the algorithm and the establishment of simple design rules. The fuel-flow minimization and velocity maximization modes of the algorithm are demonstrated on the NASA Dryden B-720 nonlinear flight simulator for the single- and multi-effector optimization cases.

Integrated Resilient Aircraft Control Project Full Scale Flight Validation

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2009-01-01

Objective: Provide validation of adaptive control law concepts through full scale flight evaluation. Technical Approach: a) Engage failure mode - destabilizing or frozen surface. b) Perform formation flight and air-to-air tracking tasks. Evaluate adaptive algorithm: a) Stability metrics. b) Model following metrics. Full scale flight testing provides an ability to validate different adaptive flight control approaches. Full scale flight testing adds credence to NASA's research efforts. A sustained research effort is required to remove the road blocks and provide adaptive control as a viable design solution for increased aircraft resilience.

Expanded envelope concepts for aircraft control-element failure detection and identification

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1988-01-01

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

Direct model reference adaptive control of robotic arms

NASA Technical Reports Server (NTRS)

Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

1993-01-01

The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric

2016-01-01

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

High Frequency Adaptive Instability Suppression Controls in a Liquid-Fueled Combustor

NASA Technical Reports Server (NTRS)

Kopasakis, George

2003-01-01

This effort extends into high frequency (>500 Hz), an earlier developed adaptive control algorithm for the suppression of thermo-acoustic instabilities in a liquidfueled combustor. The earlier work covered the development of a controls algorithm for the suppression of a low frequency (280 Hz) combustion instability based on simulations, with no hardware testing involved. The work described here includes changes to the simulation and controller design necessary to control the high frequency instability, augmentations to the control algorithm to improve its performance, and finally hardware testing and results with an experimental combustor rig developed for the high frequency case. The Adaptive Sliding Phasor Averaged Control (ASPAC) algorithm modulates the fuel flow in the combustor with a control phase that continuously slides back and forth within the phase region that reduces the amplitude of the instability. The results demonstrate the power of the method - that it can identify and suppress the instability even when the instability amplitude is buried in the noise of the combustor pressure. The successful testing of the ASPAC approach helped complete an important NASA milestone to demonstrate advanced technologies for low-emission combustors.

Phase retrieval algorithm for JWST Flight and Testbed Telescope

NASA Astrophysics Data System (ADS)

Dean, Bruce H.; Aronstein, David L.; Smith, J. Scott; Shiri, Ron; Acton, D. Scott

2006-06-01

An image-based wavefront sensing and control algorithm for the James Webb Space Telescope (JWST) is presented. The algorithm heritage is discussed in addition to implications for algorithm performance dictated by NASA's Technology Readiness Level (TRL) 6. The algorithm uses feedback through an adaptive diversity function to avoid the need for phase-unwrapping post-processing steps. Algorithm results are demonstrated using JWST Testbed Telescope (TBT) commissioning data and the accuracy is assessed by comparison with interferometer results on a multi-wave phase aberration. Strategies for minimizing aliasing artifacts in the recovered phase are presented and orthogonal basis functions are implemented for representing wavefronts in irregular hexagonal apertures. Algorithm implementation on a parallel cluster of high-speed digital signal processors (DSPs) is also discussed.

Algorithms for high-speed universal noiseless coding

NASA Technical Reports Server (NTRS)

Rice, Robert F.; Yeh, Pen-Shu; Miller, Warner

1993-01-01

This paper provides the basic algorithmic definitions and performance characterizations for a high-performance adaptive noiseless (lossless) 'coding module' which is currently under separate developments as single-chip microelectronic circuits at two NASA centers. Laboratory tests of one of these implementations recently demonstrated coding rates of up to 900 Mbits/s. Operation of a companion 'decoding module' can operate at up to half the coder's rate. The functionality provided by these modules should be applicable to most of NASA's science data. The hardware modules incorporate a powerful adaptive noiseless coder for 'standard form' data sources (i.e., sources whose symbols can be represented by uncorrelated nonnegative integers where the smaller integers are more likely than the larger ones). Performance close to data entries can be expected over a 'dynamic range' of from 1.5 to 12-15 bits/sample (depending on the implementation). This is accomplished by adaptively choosing the best of many Huffman equivalent codes to use on each block of 1-16 samples. Because of the extreme simplicity of these codes no table lookups are actually required in an implementation, thus leading to the expected very high data rate capabilities already noted.

Link Adaptation for Mitigating Earth-To-Space Propagation Effects on the NASA SCaN Testbed

NASA Technical Reports Server (NTRS)

Kilcoyne, Deirdre K.; Headley, William C.; Leffke, Zach J.; Rowe, Sonya A.; Mortensen, Dale J.; Reinhart, Richard C.; McGwier, Robert W.

2016-01-01

In Earth-to-Space communications, well-known propagation effects such as path loss and atmospheric loss can lead to fluctuations in the strength of the communications link between a satellite and its ground station. Additionally, the typically unconsidered effect of shadowing due to the geometry of the satellite and its solar panels can also lead to link degradation. As a result of these anticipated channel impairments, NASA's communication links have been traditionally designed to handle the worst-case impact of these effects through high link margins and static, lower rate, modulation formats. The work presented in this paper aims to relax these constraints by providing an improved trade-off between data rate and link margin through utilizing link adaptation. More specifically, this work provides a simulation study on the propagation effects impacting NASA's SCaN Testbed flight software-defined radio (SDR) as well as proposes a link adaptation algorithm that varies the modulation format of a communications link as its signal-to-noise ratio fluctuates. Ultimately, the models developed in this work will be utilized to conduct real-time flight experiments on-board the NASA SCaN Testbed.

Aerocapture Guidance Algorithm Comparison Campaign

NASA Technical Reports Server (NTRS)

Rousseau, Stephane; Perot, Etienne; Graves, Claude; Masciarelli, James P.; Queen, Eric

2002-01-01

The aerocapture is a promising technique for the future human interplanetary missions. The Mars Sample Return was initially based on an insertion by aerocapture. A CNES orbiter Mars Premier was developed to demonstrate this concept. Mainly due to budget constraints, the aerocapture was cancelled for the French orbiter. A lot of studies were achieved during the three last years to develop and test different guidance algorithms (APC, EC, TPC, NPC). This work was shared between CNES and NASA, with a fruitful joint working group. To finish this study an evaluation campaign has been performed to test the different algorithms. The objective was to assess the robustness, accuracy, capability to limit the load, and the complexity of each algorithm. A simulation campaign has been specified and performed by CNES, with a similar activity on the NASA side to confirm the CNES results. This evaluation has demonstrated that the numerical guidance principal is not competitive compared to the analytical concepts. All the other algorithms are well adapted to guaranty the success of the aerocapture. The TPC appears to be the more robust, the APC the more accurate, and the EC appears to be a good compromise.

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Cardullo, Frank M.; Houck, Jacob A.

2002-01-01

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

High-Performance Java Codes for Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Riley, Christopher; Chatterjee, Siddhartha; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

PredGuid+A: Orion Entry Guidance Modified for Aerocapture

NASA Technical Reports Server (NTRS)

Lafleur, Jarret

2013-01-01

PredGuid+A software was developed to enable a unique numerical predictor-corrector aerocapture guidance capability that builds on heritage Orion entry guidance algorithms. The software can be used for both planetary entry and aerocapture applications. Furthermore, PredGuid+A implements a new Delta-V minimization guidance option that can take the place of traditional targeting guidance and can result in substantial propellant savings. PredGuid+A allows the user to set a mode flag and input a target orbit's apoapsis and periapsis. Using bank angle control, the guidance will then guide the vehicle to the appropriate post-aerocapture orbit using one of two algorithms: Apoapsis Targeting or Delta-V Minimization (as chosen by the user). Recently, the PredGuid guidance algorithm was adapted for use in skip-entry scenarios for NASA's Orion multi-purpose crew vehicle (MPCV). To leverage flight heritage, most of Orion's entry guidance routines are adapted from the Apollo program.

Performance seeking control program overview

NASA Technical Reports Server (NTRS)

Orme, John S.

1995-01-01

The Performance Seeking Control (PSC) program evolved from a series of integrated propulsion-flight control research programs flown at NASA Dryden Flight Research Center (DFRC) on an F-15. The first of these was the Digital Electronic Engine Control (DEEC) program and provided digital engine controls suitable for integration. The DEEC and digital electronic flight control system of the NASA F-15 were ideally suited for integrated controls research. The Advanced Engine Control System (ADECS) program proved that integrated engine and aircraft control could improve overall system performance. The objective of the PSC program was to advance the technology for a fully integrated propulsion flight control system. Whereas ADECS provided single variable control for an average engine, PSC controlled multiple propulsion system variables while adapting to the measured engine performance. PSC was developed as a model-based, adaptive control algorithm and included four optimization modes: minimum fuel flow at constant thrust, minimum turbine temperature at constant thrust, maximum thrust, and minimum thrust. Subsonic and supersonic flight testing were conducted at NASA Dryden covering the four PSC optimization modes and over the full throttle range. Flight testing of the PSC algorithm, conducted in a series of five flight test phases, has been concluded at NASA Dryden covering all four of the PSC optimization modes. Over a three year period and five flight test phases 72 research flights were conducted. The primary objective of flight testing was to exercise each PSC optimization mode and quantify the resulting performance improvements.

An adaptive guidance algorithm for an aerodynamically assisted orbital plane change maneuver. M.S. Thesis

NASA Technical Reports Server (NTRS)

Blissit, J. A.

1986-01-01

Using analysis results from the post trajectory optimization program, an adaptive guidance algorithm is developed to compensate for density, aerodynamic and thrust perturbations during an atmospheric orbital plane change maneuver. The maneuver offers increased mission flexibility along with potential fuel savings for future reentry vehicles. Although designed to guide a proposed NASA Entry Research Vehicle, the algorithm is sufficiently generic for a range of future entry vehicles. The plane change analysis provides insight suggesting a straight-forward algorithm based on an optimized nominal command profile. Bank angle, angle of attack, and engine thrust level, ignition and cutoff times are modulated to adjust the vehicle's trajectory to achieve the desired end-conditions. A performance evaluation of the scheme demonstrates a capability to guide to within 0.05 degrees of the desired plane change and five nautical miles of the desired apogee altitude while maintaining heating constraints. The algorithm is tested under off-nominal conditions of + or -30% density biases, two density profile models, + or -15% aerodynamic uncertainty, and a 33% thrust loss and for various combinations of these conditions.

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.

2005-01-01

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Viirs Land Science Investigator-Led Processing System

NASA Astrophysics Data System (ADS)

Devadiga, S.; Mauoka, E.; Roman, M. O.; Wolfe, R. E.; Kalb, V.; Davidson, C. C.; Ye, G.

2015-12-01

The objective of the NASA's Suomi National Polar Orbiting Partnership (S-NPP) Land Science Investigator-led Processing System (Land SIPS), housed at the NASA Goddard Space Flight Center (GSFC), is to produce high quality land products from the Visible Infrared Imaging Radiometer Suite (VIIRS) to extend the Earth System Data Records (ESDRs) developed from NASA's heritage Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua satellites. In this paper we will present the functional description and capabilities of the S-NPP Land SIPS, including system development phases and production schedules, timeline for processing, and delivery of land science products based on coordination with the S-NPP Land science team members. The Land SIPS processing stream is expected to be operational by December 2016, generating land products either using the NASA science team delivered algorithms, or the "best-of" science algorithms currently in operation at NASA's Land Product Evaluation and Algorithm Testing Element (PEATE). In addition to generating the standard land science products through processing of the NASA's VIIRS Level 0 data record, the Land SIPS processing system is also used to produce a suite of near-real time products for NASA's application community. Land SIPS will also deliver the standard products, ancillary data sets, software and supporting documentation (ATBDs) to the assigned Distributed Active Archive Centers (DAACs) for archival and distribution. Quality assessment and validation will be an integral part of the Land SIPS processing system; the former being performed at Land Data Operational Product Evaluation (LDOPE) facility, while the latter under the auspices of the CEOS Working Group on Calibration & Validation (WGCV) Land Product Validation (LPV) Subgroup; adopting the best-practices and tools used to assess the quality of heritage EOS-MODIS products generated at the MODIS Adaptive Processing System (MODAPS).

Simulation evaluation of a low-altitude helicopter flight guidance system adapted for a helmet-mounted display

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Zelenka, Richard E.; Hardy, Gordon H.; Dearing, Munro G.

1992-01-01

A computer aiding concept for low-altitude helicopter flight was developed and evaluated in a real-time piloted simulation. The concept included an optimal control trajectory-generation algorithm based upon dynamic programming and a helmet-mounted display (HMD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor guidance symbology. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and advanced navigation information to determine a trajectory between mission way points that seeks valleys to minimize threat exposure. The pilot evaluation was conducted at NASA ARC moving base Vertical Motion Simulator (VMS) by pilots representing NASA, the U.S. Army, the Air Force, and the helicopter industry. The pilots manually tracked the trajectory generated by the algorithm utilizing the HMD symbology. The pilots were able to satisfactorily perform the tracking tasks while maintaining a high degree of awareness of the outside world.

Daytime O/N2 Retrieval Algorithm for the Ionospheric Connection Explorer (ICON)

NASA Astrophysics Data System (ADS)

Stephan, Andrew W.; Meier, R. R.; England, Scott L.; Mende, Stephen B.; Frey, Harald U.; Immel, Thomas J.

2018-02-01

The NASA Ionospheric Connection Explorer Far-Ultraviolet spectrometer, ICON FUV, will measure altitude profiles of the daytime far-ultraviolet (FUV) OI 135.6 nm and N2 Lyman-Birge-Hopfield (LBH) band emissions that are used to determine thermospheric density profiles and state parameters related to thermospheric composition; specifically the thermospheric column O/N2 ratio (symbolized as ΣO/N2). This paper describes the algorithm concept that has been adapted and updated from one previously applied with success to limb data from the Global Ultraviolet Imager (GUVI) on the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) mission. We also describe the requirements that are imposed on the ICON FUV to measure ΣO/N2 over any 500-km sample in daytime with a precision of better than 8.7%. We present results from orbit-simulation testing that demonstrates that the ICON FUV and our thermospheric composition retrieval algorithm can meet these requirements and provide the measurements necessary to address ICON science objectives.

Development of a space-systems network testbed

NASA Technical Reports Server (NTRS)

Lala, Jaynarayan; Alger, Linda; Adams, Stuart; Burkhardt, Laura; Nagle, Gail; Murray, Nicholas

1988-01-01

This paper describes a communications network testbed which has been designed to allow the development of architectures and algorithms that meet the functional requirements of future NASA communication systems. The central hardware components of the Network Testbed are programmable circuit switching communication nodes which can be adapted by software or firmware changes to customize the testbed to particular architectures and algorithms. Fault detection, isolation, and reconfiguration has been implemented in the Network with a hybrid approach which utilizes features of both centralized and distributed techniques to provide efficient handling of faults within the Network.

Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems

NASA Technical Reports Server (NTRS)

Houck, Jacob A.; Telban, Robert J.; Cardullo, Frank M.

1997-01-01

The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.

Development of the One-Sided Nonlinear Adaptive Doppler Shift Estimation

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.; Singh, Upendra N.; Kavaya, Michael J.; Serror, Judith A.

2009-01-01

The new development of a one-sided nonlinear adaptive shift estimation technique (NADSET) is introduced. The background of the algorithm and a brief overview of NADSET are presented. The new technique is applied to the wind parameter estimates from a 2-micron wavelength coherent Doppler lidar system called VALIDAR located in NASA Langley Research Center in Virginia. The new technique enhances wind parameters such as Doppler shift and power estimates in low Signal-To-Noise-Ratio (SNR) regimes using the estimates in high SNR regimes as the algorithm scans the range bins from low to high altitude. The original NADSET utilizes the statistics in both the lower and the higher range bins to refine the wind parameter estimates in between. The results of the two different approaches of NADSET are compared.

Development of an Unstructured Mesh Code for Flows About Complete Vehicles

NASA Technical Reports Server (NTRS)

Peraire, Jaime; Gupta, K. K. (Technical Monitor)

2001-01-01

This report describes the research work undertaken at the Massachusetts Institute of Technology, under NASA Research Grant NAG4-157. The aim of this research is to identify effective algorithms and methodologies for the efficient and routine solution of flow simulations about complete vehicle configurations. For over ten years we have received support from NASA to develop unstructured mesh methods for Computational Fluid Dynamics. As a result of this effort a methodology based on the use of unstructured adapted meshes of tetrahedra and finite volume flow solvers has been developed. A number of gridding algorithms, flow solvers, and adaptive strategies have been proposed. The most successful algorithms developed from the basis of the unstructured mesh system FELISA. The FELISA system has been extensively for the analysis of transonic and hypersonic flows about complete vehicle configurations. The system is highly automatic and allows for the routine aerodynamic analysis of complex configurations starting from CAD data. The code has been parallelized and utilizes efficient solution algorithms. For hypersonic flows, a version of the code which incorporates real gas effects, has been produced. The FELISA system is also a component of the STARS aeroservoelastic system developed at NASA Dryden. One of the latest developments before the start of this grant was to extend the system to include viscous effects. This required the development of viscous generators, capable of generating the anisotropic grids required to represent boundary layers, and viscous flow solvers. We show some sample hypersonic viscous computations using the developed viscous generators and solvers. Although this initial results were encouraging it became apparent that in order to develop a fully functional capability for viscous flows, several advances in solution accuracy, robustness and efficiency were required. In this grant we set out to investigate some novel methodologies that could lead to the required improvements. In particular we focused on two fronts: (1) finite element methods and (2) iterative algebraic multigrid solution techniques.

Space Launch System Implementation of Adaptive Augmenting Control

NASA Technical Reports Server (NTRS)

Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.

2014-01-01

Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

Adaptive Controls Method Demonstrated for the Active Suppression of Instabilities in Engine Combustors

NASA Technical Reports Server (NTRS)

Kopasakis, George

2004-01-01

An adaptive feedback control method was demonstrated that suppresses thermoacoustic instabilities in a liquid-fueled combustor of a type used in aircraft engines. Extensive research has been done to develop lean-burning (low fuel-to-air ratio) combustors that can reduce emissions throughout the mission cycle to reduce the environmental impact of aerospace propulsion systems. However, these lean-burning combustors are susceptible to thermoacoustic instabilities (high-frequency pressure waves), which can fatigue combustor components and even the downstream turbine blades. This can significantly decrease the safe operating lives of the combustor and turbine. Thus, suppressing the thermoacoustic combustor instabilities is an enabling technology for lean, low-emissions combustors under NASA's Propulsion and Power Program. This control methodology has been developed and tested in a partnership of the NASA Glenn Research Center, Pratt & Whitney, United Technologies Research Center, and the Georgia Institute of Technology. Initial combustor rig testing of the controls algorithm was completed during 2002. Subsequently, the test results were analyzed and improvements to the method were incorporated in 2003, which culminated in the final status of this controls algorithm. This control methodology is based on adaptive phase shifting. The combustor pressure oscillations are sensed and phase shifted, and a high-frequency fuel valve is actuated to put pressure oscillations into the combustor to cancel pressure oscillations produced by the instability.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations of Adverse Interactions Using a Piloted Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curt; Miller, Chris; Wall, John H.; Vanzwieten, Tannen S.; Gilligan, Eric; Orr, Jeb S.

2015-01-01

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority. Two NASA research pilots flew a total of twenty five constant pitch-rate trajectories using a prototype manual steering mode with and without adaptive control.

A Perspective on Computational Aerothermodynamics at NASA

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2007-01-01

The evolving role of computational aerothermodynamics (CA) within NASA over the past 20 years is reviewed. The presentation highlights contributions to understanding the Space Shuttle pitching moment anomaly observed in the first shuttle flight, prediction of a static instability for Mars Pathfinder, and the use of CA for damage assessment in post-Columbia mission support. In the view forward, several current challenges in computational fluid dynamics and aerothermodynamics for hypersonic vehicle applications are discussed. Example simulations are presented to illustrate capabilities and limitations. Opportunities to advance the state-of-art in algorithms, grid generation and adaptation, and code validation are identified.

A User's Guide to AMR1D: An Instructional Adaptive Mesh Refinement Code for Unstructured Grids

NASA Technical Reports Server (NTRS)

deFainchtein, Rosalinda

1996-01-01

This report documents the code AMR1D, which is currently posted on the World Wide Web (http://sdcd.gsfc.nasa.gov/ESS/exchange/contrib/de-fainchtein/adaptive _mesh_refinement.html). AMR1D is a one-dimensional finite element fluid-dynamics solver, capable of adaptive mesh refinement (AMR). It was written as an instructional tool for AMR on unstructured mesh codes. It is meant to illustrate the minimum requirements for AMR on more than one dimension. For that purpose, it uses the same type of data structure that would be necessary on a two-dimensional AMR code (loosely following the algorithm described by Lohner).

Space Launch System Implementation of Adaptive Augmenting Control

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Wall, John H.; Orr, Jeb S.

2014-01-01

Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to robustly demonstrate stable and high performance flight. On its development path to preliminary design review (PDR), the stability of the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant dynamics. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an adaptive augmenting control (AAC) algorithm previously presented by Orr and VanZwieten, has been shown to extend the envelope of failures and flight anomalies for which the SLS control system can accommodate while maintaining a direct link to flight control stability criteria (e.g. gain & phase margin). In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the SLS digital 3-axis autopilot, including existing load-relief elements, and necessary steps for integration with the production flight software prototype have been implemented. Several updates to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

Systematic Benchmarking of Diagnostic Technologies for an Electrical Power System

NASA Technical Reports Server (NTRS)

Kurtoglu, Tolga; Jensen, David; Poll, Scott

2009-01-01

Automated health management is a critical functionality for complex aerospace systems. A wide variety of diagnostic algorithms have been developed to address this technical challenge. Unfortunately, the lack of support to perform large-scale V&V (verification and validation) of diagnostic technologies continues to create barriers to effective development and deployment of such algorithms for aerospace vehicles. In this paper, we describe a formal framework developed for benchmarking of diagnostic technologies. The diagnosed system is the Advanced Diagnostics and Prognostics Testbed (ADAPT), a real-world electrical power system (EPS), developed and maintained at the NASA Ames Research Center. The benchmarking approach provides a systematic, empirical basis to the testing of diagnostic software and is used to provide performance assessment for different diagnostic algorithms.

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

NASA Technical Reports Server (NTRS)

Matthews, Bryan L.; Srivastava, Ashok N.

2010-01-01

Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 2

NASA Technical Reports Server (NTRS)

Lea, Robert N. (Editor); Villarreal, James A. (Editor)

1991-01-01

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Texas, Houston. Topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

Probabilistic Structural Analysis Program

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

2010-01-01

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

Methods for Probabilistic Fault Diagnosis: An Electrical Power System Case Study

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Health management systems that more accurately and quickly diagnose faults that may occur in different technical systems on-board a vehicle will play a key role in the success of future NASA missions. We discuss in this paper the diagnosis of abrupt continuous (or parametric) faults within the context of probabilistic graphical models, more specifically Bayesian networks that are compiled to arithmetic circuits. This paper extends our previous research, within the same probabilistic setting, on diagnosis of abrupt discrete faults. Our approach and diagnostic algorithm ProDiagnose are domain-independent; however we use an electrical power system testbed called ADAPT as a case study. In one set of ADAPT experiments, performed as part of the 2009 Diagnostic Challenge, our system turned out to have the best performance among all competitors. In a second set of experiments, we show how we have recently further significantly improved the performance of the probabilistic model of ADAPT. While these experiments are obtained for an electrical power system testbed, we believe they can easily be transitioned to real-world systems, thus promising to increase the success of future NASA missions.

Classification of posture maintenance data with fuzzy clustering algorithms

NASA Technical Reports Server (NTRS)

Bezdek, James C.

1991-01-01

Sensory inputs from the visual, vestibular, and proprioreceptive systems are integrated by the central nervous system to maintain postural equilibrium. Sustained exposure to microgravity causes neurosensory adaptation during spaceflight, which results in decreased postural stability until readaptation occurs upon return to the terrestrial environment. Data which simulate sensory inputs under various conditions were collected in conjunction with JSC postural control studies using a Tilt-Translation Device (TTD). The University of West Florida proposed applying the Fuzzy C-Means Clustering (FCM) Algorithms to this data with a view towards identifying various states and stages. Data supplied by NASA/JSC were submitted to the FCM algorithms in an attempt to identify and characterize cluster substructure in a mixed ensemble of pre- and post-adaptational TTD data. Following several unsuccessful trials with FCM using a full 11 dimensional data set, a set of two channels (features) were found to enable FCM to separate pre- from post-adaptational TTD data. The main conclusions are that: (1) FCM seems able to separate pre- from post-TTD subject no. 2 on the one trial that was used, but only in certain subintervals of time; and (2) Channels 2 (right rear transducer force) and 8 (hip sway bar) contain better discrimination information than other supersets and combinations of the data that were tried so far.

In-Flight Suppression of a De-Stabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

Wall, John; VanZwieten, Tannen; Giiligan Eric; Miller, Chris; Hanson, Curtis; Orr, Jeb

2015-01-01

Adaptive Augmenting Control (AAC) has been developed for NASA's Space Launch System (SLS) family of launch vehicles and implemented as a baseline part of its flight control system (FCS). To raise the technical readiness level of the SLS AAC algorithm, the Launch Vehicle Adaptive Control (LVAC) flight test program was conducted in which the SLS FCS prototype software was employed to control the pitch axis of Dryden's specially outfitted F/A-18, the Full Scale Advanced Systems Test Bed (FAST). This presentation focuses on a set of special test cases which demonstrate the successful mitigation of the unstable coupling of an F/A-18 airframe structural mode with the SLS FCS.

Runway Incursion Prevention for General Aviation Operations

NASA Technical Reports Server (NTRS)

Jones, Denise R.; Prinzel, Lawrence J., III

2006-01-01

A Runway Incursion Prevention System (RIPS) and additional incursion detection algorithm were adapted for general aviation operations and evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in the fall of 2005. RIPS has been designed to enhance surface situation awareness and provide cockpit alerts of potential runway conflicts in order to prevent runway incidents while also improving operational capability. The purpose of the study was to evaluate the airborne incursion detection algorithms and associated alerting and airport surface display concepts for general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Runway Incursion Prevention System for General Aviation Operations

NASA Technical Reports Server (NTRS)

Jones, Denise R.; Prinzel III, Lawrence J.

2006-01-01

A Runway Incursion Prevention System (RIPS) and additional incursion detection algorithm were adapted for general aviation operations and evaluated in a simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in the fall of 2005. RIPS has been designed to enhance surface situation awareness and provide cockpit alerts of potential runway conflicts in order to prevent runway incidents while also improving operational capability. The purpose of the study was to evaluate the airborne incursion detection algorithms and associated alerting and airport surface display concepts for general aviation operations. This paper gives an overview of the system, simulation study, and test results.

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA Technical Reports Server (NTRS)

Rash, James

2014-01-01

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.

2012-01-01

Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

A generic efficient adaptive grid scheme for rocket propulsion modeling

NASA Technical Reports Server (NTRS)

Mo, J. D.; Chow, Alan S.

1993-01-01

The objective of this research is to develop an efficient, time-accurate numerical algorithm to discretize the Navier-Stokes equations for the predictions of internal one-, two-dimensional and axisymmetric flows. A generic, efficient, elliptic adaptive grid generator is implicitly coupled with the Lower-Upper factorization scheme in the development of ALUNS computer code. The calculations of one-dimensional shock tube wave propagation and two-dimensional shock wave capture, wave-wave interactions, shock wave-boundary interactions show that the developed scheme is stable, accurate and extremely robust. The adaptive grid generator produced a very favorable grid network by a grid speed technique. This generic adaptive grid generator is also applied in the PARC and FDNS codes and the computational results for solid rocket nozzle flowfield and crystal growth modeling by those codes will be presented in the conference, too. This research work is being supported by NASA/MSFC.

Operational Implementation of Sea Ice Concentration Estimates from the AMSR2 Sensor

NASA Technical Reports Server (NTRS)

Meier, Walter N.; Stewart, J. Scott; Liu, Yinghui; Key, Jeffrey; Miller, Jeffrey A.

2017-01-01

An operation implementation of a passive microwave sea ice concentration algorithm to support NOAA's operational mission is presented. The NASA team 2 algorithm, previously developed for the NASA advanced microwave scanning radiometer for the Earth observing system (AMSR-E) product suite, is adapted for operational use with the JAXA AMSR2 sensor through several enhancements. First, the algorithm is modified to process individual swaths and provide concentration from the most recent swaths instead of a 24-hour average. A latency (time since observation) field and a 24-hour concentration range (maximum-minimum) are included to provide indications of data timeliness and variability. Concentration from the Bootstrap algorithm is a secondary field to provide complementary sea ice information. A quality flag is implemented to provide information on interpolation, filtering, and other quality control steps. The AMSR2 concentration fields are compared with a different AMSR2 passive microwave product, and then validated via comparison with sea ice concentration from the Suomi visible and infrared imaging radiometer suite. This validation indicates the AMSR2 concentrations have a bias of 3.9% and an RMSE of 11.0% in the Arctic, and a bias of 4.45% and RMSE of 8.8% in the Antarctic. In most cases, the NOAA operational requirements for accuracy are met. However, in low-concentration regimes, such as during melt and near the ice edge, errors are higher because of the limitations of passive microwave sensors and the algorithm retrieval.

Robust, Practical Adaptive Control for Launch Vehicles

NASA Technical Reports Server (NTRS)

Orr, Jeb. S.; VanZwieten, Tannen S.

2012-01-01

A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA Technical Reports Server (NTRS)

Rash, James L.

2010-01-01

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Advances in Orion's On-Orbit Guidance and Targeting System Architecture

NASA Technical Reports Server (NTRS)

Scarritt, Sara K.; Fill, Thomas; Robinson, Shane

2015-01-01

NASA's manned spaceflight programs have a rich history of advancing onboard guidance and targeting technology. In order to support future missions, the guidance and targeting architecture for the Orion Multi-Purpose Crew Vehicle must be able to operate in complete autonomy, without any support from the ground. Orion's guidance and targeting system must be sufficiently flexible to easily adapt to a wide array of undecided future missions, yet also not cause an undue computational burden on the flight computer. This presents a unique design challenge from the perspective of both algorithm development and system architecture construction. The present work shows how Orion's guidance and targeting system addresses these challenges. On the algorithm side, the system advances the state-of-the-art by: (1) steering burns with a simple closed-loop guidance strategy based on Shuttle heritage, and (2) planning maneuvers with a cutting-edge two-level targeting routine. These algorithms are then placed into an architecture designed to leverage the advantages of each and ensure that they function in concert with one another. The resulting system is characterized by modularity and simplicity. As such, it is adaptable to the on-orbit phases of any future mission that Orion may attempt.

Launch Vehicle Manual Steering with Adaptive Augmenting Control:In-Flight Evaluations of Adverse Interactions Using a Piloted Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curt; Miller, Chris; Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Orr, Jeb S.

2015-01-01

An Adaptive Augmenting Control (AAC) algorithm for the Space Launch System (SLS) has been developed at the Marshall Space Flight Center (MSFC) as part of the launch vehicle's baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a potential manual steering mode were also investigated by giving the pilot trajectory deviation cues and pitch rate command authority, which is the subject of this paper. Two NASA research pilots flew a total of 25 constant pitch rate trajectories using a prototype manual steering mode with and without adaptive control, evaluating six different nominal and off-nominal test case scenarios. Pilot comments and PIO ratings were given following each trajectory and correlated with aircraft state data and internal controller signals post-flight.

Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 1

NASA Technical Reports Server (NTRS)

Lea, Robert N. (Editor); Villarreal, James (Editor)

1991-01-01

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Houston, Clear Lake. The workshop was held April 11 to 13 at the Johnson Space Flight Center. Technical topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

In-Flight Suppression of an Unstable F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Gilligan, Eric T.; Wall, John H.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off-nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using post-flight frequency-domain reconstruction, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

NASA Tech Briefs, July 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Wirelessly Interrogated Wear or Temperature Sensors; Processing Nanostructured Sensors Using Microfabrication Techniques; Optical Pointing Sensor; Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging; High-Temperature Optical Sensor; Integral Battery Power Limiting Circuit for Intrinsically Safe Applications; Configurable Multi-Purpose Processor; Squeezing Alters Frequency Tuning of WGM Optical Resonator; Automated Computer Access Request System; Range Safety for an Autonomous Flight Safety System; Fast and Easy Searching of Files in Unisys 2200 Computers; Parachute Drag Model; Evolutionary Scheduler for the Deep Space Network; Modular Habitats Comprising Rigid and Inflatable Modules; More About N2O-Based Propulsion and Breathable-Gas Systems; Ultrasonic/Sonic Rotary-Hammer Drills; Miniature Piezoelectric Shaker for Distribution of Unconsolidated Samples to Instrument Cells; Lunar Soil Particle Separator; Advanced Aerobots for Scientific Exploration; Miniature Bioreactor System for Long-Term Cell Culture; Electrochemical Detection of Multiple Bioprocess Analytes; Fabrication and Modification of Nanoporous Silicon Particles; High-Altitude Hydration System; Photon Counting Using Edge-Detection Algorithm; Holographic Vortex Coronagraph; Optical Structural Health Monitoring Device; Fuel-Cell Power Source Based on Onboard Rocket Propellants; Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments; Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS; Improved Speed and Functionality of a 580-GHz Imaging Radar; Bolometric Device Based on Fluxoid Quantization; Algorithms for Learning Preferences for Sets of Objects; Model for Simulating a Spiral Software-Development Process; Algorithm That Synthesizes Other Algorithms for Hashing; Algorithms for High-Speed Noninvasive Eye-Tracking System; and Adapting ASPEN for Orbital Express.

Unstructured Mesh Methods for the Simulation of Hypersonic Flows

NASA Technical Reports Server (NTRS)

Peraire, Jaime; Bibb, K. L. (Technical Monitor)

2001-01-01

This report describes the research work undertaken at the Massachusetts Institute of Technology. The aim of this research is to identify effective algorithms and methodologies for the efficient and routine solution of hypersonic viscous flows about re-entry vehicles. For over ten years we have received support from NASA to develop unstructured mesh methods for Computational Fluid Dynamics. As a result of this effort a methodology based on the use, of unstructured adapted meshes of tetrahedra and finite volume flow solvers has been developed. A number of gridding algorithms flow solvers, and adaptive strategies have been proposed. The most successful algorithms developed from the basis of the unstructured mesh system FELISA. The FELISA system has been extensively for the analysis of transonic and hypersonic flows about complete vehicle configurations. The system is highly automatic and allows for the routine aerodynamic analysis of complex configurations starting from CAD data. The code has been parallelized and utilizes efficient solution algorithms. For hypersonic flows, a version of the, code which incorporates real gas effects, has been produced. One of the latest developments before the start of this grant was to extend the system to include viscous effects. This required the development of viscous generators, capable of generating the anisotropic grids required to represent boundary layers, and viscous flow solvers. In figures I and 2, we show some sample hypersonic viscous computations using the developed viscous generators and solvers. Although these initial results were encouraging, it became apparent that in order to develop a fully functional capability for viscous flows, several advances in gridding, solution accuracy, robustness and efficiency were required. As part of this research we have developed: 1) automatic meshing techniques and the corresponding computer codes have been delivered to NASA and implemented into the GridEx system, 2) a finite element algorithm for the solution of the viscous compressible flow equations which can solve flows all the way down to the incompressible limit and that can use higher order (quadratic) approximations leading to highly accurate answers, and 3) and iterative algebraic multigrid solution techniques.

Concurrent extensions to the FORTRAN language for parallel programming of computational fluid dynamics algorithms

NASA Technical Reports Server (NTRS)

Weeks, Cindy Lou

1986-01-01

Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.

Spheres: from Ground Development to ISS Operations

NASA Technical Reports Server (NTRS)

Katterhagen, A.

2016-01-01

SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) is an internal International Space Station (ISS) Facility that supports multiple investigations for the development of multi-spacecraft and robotic control algorithms. The SPHERES National Lab Facility aboard ISS is managed and operated by NASA Ames Research Center (ARC) at Moffett Field California. The SPHERES Facility on ISS consists of three self-contained eight-inch diameter free-floating satellites which perform the various flight algorithms and serve as a platform to support the integration of experimental hardware. SPHERES has served to mature the adaptability of control algorithms of future formation flight missions in microgravity (6 DOF (Degrees of Freedom) / long duration microgravity), demonstrate key close-proximity formation flight and rendezvous and docking maneuvers, understand fault diagnosis and recovery, improve the field of human telerobotic operation and control, and lessons learned on ISS have significant impact on ground robotics, mapping, localization, and sensing in three-dimensions - among several other areas of study.

Optimal design of composite hip implants using NASA technology

NASA Technical Reports Server (NTRS)

Blake, T. A.; Saravanos, D. A.; Davy, D. T.; Waters, S. A.; Hopkins, D. A.

1993-01-01

Using an adaptation of NASA software, we have investigated the use of numerical optimization techniques for the shape and material optimization of fiber composite hip implants. The original NASA inhouse codes, were originally developed for the optimization of aerospace structures. The adapted code, which was called OPORIM, couples numerical optimization algorithms with finite element analysis and composite laminate theory to perform design optimization using both shape and material design variables. The external and internal geometry of the implant and the surrounding bone is described with quintic spline curves. This geometric representation is then used to create an equivalent 2-D finite element model of the structure. Using laminate theory and the 3-D geometric information, equivalent stiffnesses are generated for each element of the 2-D finite element model, so that the 3-D stiffness of the structure can be approximated. The geometric information to construct the model of the femur was obtained from a CT scan. A variety of test cases were examined, incorporating several implant constructions and design variable sets. Typically the code was able to produce optimized shape and/or material parameters which substantially reduced stress concentrations in the bone adjacent of the implant. The results indicate that this technology can provide meaningful insight into the design of fiber composite hip implants.

Fast and Adaptive Lossless On-Board Hyperspectral Data Compression System for Space Applications

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh; Bakhshi, Alireza; Keymeulen, Didier; Klimesh, Matthew

2009-01-01

Efficient on-board lossless hyperspectral data compression reduces the data volume necessary to meet NASA and DoD limited downlink capabilities. The techniques also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware, which makes it practical for flight implementations of pushbroom instruments. A prototype of the compressor (and decompressor) of the algorithm is available in software, but this implementation may not meet speed and real-time requirements of some space applications. Hardware acceleration provides performance improvements of 10x-100x vs. the software implementation (about 1M samples/sec on a Pentium IV machine). This paper describes a hardware implementation of the JPL-developed 'Fast Lossless' compression algorithm on a Field Programmable Gate Array (FPGA). The FPGA implementation targets the current state of the art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for Space applications.

Hardware Implementation of Lossless Adaptive and Scalable Hyperspectral Data Compression for Space

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh; Keymeulen, Didier; Bakhshi, Alireza; Klimesh, Matthew

2009-01-01

On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware. A modified form of the algorithm that is better suited for data from pushbroom instruments is generally appropriate for flight implementation. A scalable field programmable gate array (FPGA) hardware implementation was developed. The FPGA implementation achieves a throughput performance of 58 Msamples/sec, which can be increased to over 100 Msamples/sec in a parallel implementation that uses twice the hardware resources This paper describes the hardware implementation of the 'Modified Fast Lossless' compression algorithm on an FPGA. The FPGA implementation targets the current state-of-the-art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for space applications.

Adaptive Flight Control for Aircraft Safety Enhancements

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.

2008-01-01

This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.

DVB-S2 Experiment over NASA's Space Network

NASA Technical Reports Server (NTRS)

Downey, Joseph A.; Evans, Michael A.; Tollis, Nicholas S.

2017-01-01

The commercial DVB-S2 standard was successfully demonstrated over NASAs Space Network (SN) and the Tracking Data and Relay Satellite System (TDRSS) during testing conducted September 20-22nd, 2016. This test was a joint effort between NASA Glenn Research Center (GRC) and Goddard Space Flight Center (GSFC) to evaluate the performance of DVB-S2 as an alternative to traditional NASA SN waveforms. Two distinct sets of tests were conducted: one was sourced from the Space Communication and Navigation (SCaN) Testbed, an external payload on the International Space Station, and the other was sourced from GRCs S-band ground station to emulate a Space Network user through TDRSS. In both cases, a commercial off-the-shelf (COTS) receiver made by Newtec was used to receive the signal at White Sands Complex. Using SCaN Testbed, peak data rates of 5.7 Mbps were demonstrated. Peak data rates of 33 Mbps were demonstrated over the GRC S-band ground station through a 10MHz channel over TDRSS, using 32-amplitude phase shift keying (APSK) and a rate 89 low density parity check (LDPC) code. Advanced features of the DVB-S2 standard were evaluated, including variable and adaptive coding and modulation (VCMACM), as well as an adaptive digital pre-distortion (DPD) algorithm. These features provided additional data throughput and increased link performance reliability. This testing has shown that commercial standards are a viable, low-cost alternative for future Space Network users.

On the use of controls for subsonic transport performance improvement: Overview and future directions

NASA Technical Reports Server (NTRS)

Gilyard, Glenn; Espana, Martin

1994-01-01

Increasing competition among airline manufacturers and operators has highlighted the issue of aircraft efficiency. Fewer aircraft orders have led to an all-out efficiency improvement effort among the manufacturers to maintain if not increase their share of the shrinking number of aircraft sales. Aircraft efficiency is important in airline profitability and is key if fuel prices increase from their current low. In a continuing effort to improve aircraft efficiency and develop an optimal performance technology base, NASA Dryden Flight Research Center developed and flight tested an adaptive performance seeking control system to optimize the quasi-steady-state performance of the F-15 aircraft. The demonstrated technology is equally applicable to transport aircraft although with less improvement. NASA Dryden, in transitioning this technology to transport aircraft, is specifically exploring the feasibility of applying adaptive optimal control techniques to performance optimization of redundant control effectors. A simulation evaluation of a preliminary control law optimizes wing-aileron camber for minimum net aircraft drag. Two submodes are evaluated: one to minimize fuel and the other to maximize velocity. This paper covers the status of performance optimization of the current fleet of subsonic transports. Available integrated controls technologies are reviewed to define approaches using active controls. A candidate control law for adaptive performance optimization is presented along with examples of algorithm operation.

Fuzzy logic and neural network technologies

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Lea, Robert N.; Savely, Robert T.

1992-01-01

Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

NASA Technical Reports Server (NTRS)

Padgett, Mary L. (Editor)

1993-01-01

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

Reconfigurable Model Execution in the OpenMDAO Framework

NASA Technical Reports Server (NTRS)

Hwang, John T.

2017-01-01

NASA's OpenMDAO framework facilitates constructing complex models and computing their derivatives for multidisciplinary design optimization. Decomposing a model into components that follow a prescribed interface enables OpenMDAO to assemble multidisciplinary derivatives from the component derivatives using what amounts to the adjoint method, direct method, chain rule, global sensitivity equations, or any combination thereof, using the MAUD architecture. OpenMDAO also handles the distribution of processors among the disciplines by hierarchically grouping the components, and it automates the data transfer between components that are on different processors. These features have made OpenMDAO useful for applications in aircraft design, satellite design, wind turbine design, and aircraft engine design, among others. This paper presents new algorithms for OpenMDAO that enable reconfigurable model execution. This concept refers to dynamically changing, during execution, one or more of: the variable sizes, solution algorithm, parallel load balancing, or set of variables-i.e., adding and removing components, perhaps to switch to a higher-fidelity sub-model. Any component can reconfigure at any point, even when running in parallel with other components, and the reconfiguration algorithm presented here performs the synchronized updates to all other components that are affected. A reconfigurable software framework for multidisciplinary design optimization enables new adaptive solvers, adaptive parallelization, and new applications such as gradient-based optimization with overset flow solvers and adaptive mesh refinement. Benchmarking results demonstrate the time savings for reconfiguration compared to setting up the model again from scratch, which can be significant in large-scale problems. Additionally, the new reconfigurability feature is applied to a mission profile optimization problem for commercial aircraft where both the parametrization of the mission profile and the time discretization are adaptively refined, resulting in computational savings of roughly 10% and the elimination of oscillations in the optimized altitude profile.

F-8C adaptive flight control laws

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Harvey, C. A.; Stein, G.; Carlson, D. N.; Hendrick, R. C.

1977-01-01

Three candidate digital adaptive control laws were designed for NASA's F-8C digital flyby wire aircraft. Each design used the same control laws but adjusted the gains with a different adaptative algorithm. The three adaptive concepts were: high-gain limit cycle, Liapunov-stable model tracking, and maximum likelihood estimation. Sensors were restricted to conventional inertial instruments (rate gyros and accelerometers) without use of air-data measurements. Performance, growth potential, and computer requirements were used as criteria for selecting the most promising of these candidates for further refinement. The maximum likelihood concept was selected primarily because it offers the greatest potential for identifying several aircraft parameters and hence for improved control performance in future aircraft application. In terms of identification and gain adjustment accuracy, the MLE design is slightly superior to the other two, but this has no significant effects on the control performance achievable with the F-8C aircraft. The maximum likelihood design is recommended for flight test, and several refinements to that design are proposed.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Refinement and evaluation of helicopter real-time self-adaptive active vibration controller algorithms

NASA Technical Reports Server (NTRS)

Davis, M. W.

1984-01-01

A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.

Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring. Degree awarded by Toledo Univ., May 2002

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.

2003-01-01

A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they are to damage. Another finding was that clear threshold limits must be established for diagnostic tools. Based on additional experimental data obtained from the NASA Glenn Spiral Bevel Gear Fatigue Rig, the methodology developed in this study can be successfully implemented on other geared systems.

Aging Aircraft 2005, The Joint NASA/FAA/DOD Conference on Aging Aircraft, Decision algorithms for Electrical Wiring Interconnect Systems (EWIS)Fault Detection

DTIC Science & Technology

2005-02-03

Aging Aircraft 2005 The 8th Joint NASA /FAA/DOD Conference on Aging Aircraft Decision Algorithms for Electrical Wiring Interconnect Systems (EWIS...SUBTITLE Aging Aircraft 2005, The 8th Joint NASA /FAA/DOD Conference on Aging Aircraft, Decision algorithms for Electrical Wiring Interconnect...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) NASA Langley Research Center, 8W. Taylor St., M/S 190 Hampton, VA 23681 and NAVAIR

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

XML in an Adaptive Framework for Instrument Control

NASA Technical Reports Server (NTRS)

Ames, Troy J.

2004-01-01

NASA Goddard Space Flight Center is developing an extensible framework for instrument command and control, known as Instrument Remote Control (IRC), that combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms.

Path Planning Algorithms for the Adaptive Sensor Fleet

NASA Technical Reports Server (NTRS)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

Towards improving the NASA standard soil moisture retrieval algorithm and product

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Jackson, T. J.; Njoku, E. G.; Bindlish, R.; Cosh, M. H.; Chan, S.

2013-12-01

Soil moisture mapping using passive-based microwave remote sensing techniques has proven to be one of the most effective ways of acquiring reliable global soil moisture information on a routine basis. An important step in this direction was made by the launch of the Advanced Microwave Scanning Radiometer on the NASA's Earth Observing System Aqua satellite (AMSR-E). Along with the standard NASA algorithm and operational AMSR-E product, the easy access and availability of the AMSR-E data promoted the development and distribution of alternative retrieval algorithms and products. Several evaluation studies have demonstrated issues with the standard NASA AMSR-E product such as dampened temporal response and limited range of the final retrievals and noted that the available global passive-based algorithms, even though based on the same electromagnetic principles, produce different results in terms of accuracy and temporal dynamics. Our goal is to identify the theoretical causes that determine the reduced sensitivity of the NASA AMSR-E product and outline ways to improve the operational NASA algorithm, if possible. Properly identifying the underlying reasons that cause the above mentioned features of the NASA AMSR-E product and differences between the alternative algorithms requires a careful examination of the theoretical basis of each approach. Specifically, the simplifying assumptions and parametrization approaches adopted by each algorithm to reduce the dimensionality of unknowns and characterize the observing system. Statistically-based error analyses, which are useful and necessary, provide information on the relative accuracy of each product but give very little information on the theoretical causes, knowledge that is essential for algorithm improvement. Thus, we are currently examining the possibility of improving the standard NASA AMSR-E global soil moisture product by conducting a thorough theoretically-based review of and inter-comparisons between several well established global retrieval techniques. A detailed discussion focused on the theoretical basis of each approach and algorithms sensitivity to assumptions and parametrization approaches will be presented. USDA is an equal opportunity provider and employer.

Multi-limbed locomotion systems for space construction and maintenance

NASA Technical Reports Server (NTRS)

Waldron, K. J.; Klein, C. A.

1987-01-01

A well developed technology of coordination of multi-limbed locomotory systems is now available. Results from a NASA sponsored study of several years ago are presented. This was a simulation study of a three-limbed locomotion/manipulation system. Each limb had six degrees of freedom and could be used either as a locomotory grasping hand-holds, or as a manipulator. The focus of the study was kinematic coordination algorithms. The presentation will also include very recent results from the Adaptive Suspension Vehicle Project. The Adaptive Suspension Vehicle (ASV) is a legged locomotion system designed for terrestrial use which is capable of operating in completely unstructured terrain in either a teleoperated or operator-on-board mode. Future development may include autonomous operation. The ASV features a very advanced coordination and control system which could readily be adapted to operation in space. An inertial package with a vertical gyro, and rate gyros and accelerometers on three orthogonal axes provides body position information at high bandwidth. This is compared to the operator's commands, injected via a joystick to provide a commanded force system on the vehicle's body. This system is, in turn, decomposed by a coordination algorithm into force commands to those legs which are in contact with the ground.

Airborne Wind Profiling Algorithms for the Pulsed 2-Micron Coherent Doppler Lidar at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.; Kavaya, Michael J.; Ray, Taylor J.

2013-01-01

Two versions of airborne wind profiling algorithms for the pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. Each algorithm utilizes different number of line-of-sight (LOS) lidar returns while compensating the adverse effects of different coordinate systems between the aircraft and the Earth. One of the two algorithms APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) estimates wind products using two LOSs. The other algorithm utilizes five LOSs. The airborne lidar data were acquired during the NASA's Genesis and Rapid Intensification Processes (GRIP) campaign in 2010. The wind profile products from the two algorithms are compared with the dropsonde data to validate their results.

SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters

NASA Technical Reports Server (NTRS)

McKinna, Lachlan I. W.; Werdell, P. Jeremy; Fearns, Peter R. C. S.; Weeks, Scarla J.; Reichstetter, Martina; Franz, Bryan A.; Shea, Donald M.; Feldman, Gene C.

2014-01-01

Ocean color remote sensing provides synoptic-scale, near-daily observations of marine inherent optical properties (IOPs). Whilst contemporary ocean color algorithms are known to perform well in deep oceanic waters, they have difficulty operating in optically clear, shallow marine environments where light reflected from the seafloor contributes to the water-leaving radiance. The effect of benthic reflectance in optically shallow waters is known to adversely affect algorithms developed for optically deep waters [1, 2]. Whilst adapted versions of optically deep ocean color algorithms have been applied to optically shallow regions with reasonable success [3], there is presently no approach that directly corrects for bottom reflectance using existing knowledge of bathymetry and benthic albedo.To address the issue of optically shallow waters, we have developed a semi-analytical ocean color inversion algorithm: the Shallow Water Inversion Model (SWIM). SWIM uses existing bathymetry and a derived benthic albedo map to correct for bottom reflectance using the semi-analytical model of Lee et al [4]. The algorithm was incorporated into the NASA Ocean Biology Processing Groups L2GEN program and tested in optically shallow waters of the Great Barrier Reef, Australia. In-lieu of readily available in situ matchup data, we present a comparison between SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Property Algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA).

Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rohrs, C. E.

1982-01-01

Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Some practical universal noiseless coding techniques, part 3, module PSl14,K+

NASA Technical Reports Server (NTRS)

Rice, Robert F.

1991-01-01

The algorithmic definitions, performance characterizations, and application notes for a high-performance adaptive noiseless coding module are provided. Subsets of these algorithms are currently under development in custom very large scale integration (VLSI) at three NASA centers. The generality of coding algorithms recently reported is extended. The module incorporates a powerful adaptive noiseless coder for Standard Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers, where smaller integers are more likely than the larger ones). Coders can be specified to provide performance close to the data entropy over any desired dynamic range (of entropy) above 0.75 bit/sample. This is accomplished by adaptively choosing the best of many efficient variable-length coding options to use on each short block of data (e.g., 16 samples) All code options used for entropies above 1.5 bits/sample are 'Huffman Equivalent', but they require no table lookups to implement. The coding can be performed directly on data that have been preprocessed to exhibit the characteristics of a standard source. Alternatively, a built-in predictive preprocessor can be used where applicable. This built-in preprocessor includes the familiar 1-D predictor followed by a function that maps the prediction error sequences into the desired standard form. Additionally, an external prediction can be substituted if desired. A broad range of issues dealing with the interface between the coding module and the data systems it might serve are further addressed. These issues include: multidimensional prediction, archival access, sensor noise, rate control, code rate improvements outside the module, and the optimality of certain internal code options.

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Informed Source Separation of Atmospheric and Surface Signal Contributions in Shortwave Hyperspectral Imagery using Non-negative Matrix Factorization

NASA Astrophysics Data System (ADS)

Wright, L.; Coddington, O.; Pilewskie, P.

2015-12-01

Current challenges in Earth remote sensing require improved instrument spectral resolution, spectral coverage, and radiometric accuracy. Hyperspectral instruments, deployed on both aircraft and spacecraft, are a growing class of Earth observing sensors designed to meet these challenges. They collect large amounts of spectral data, allowing thorough characterization of both atmospheric and surface properties. The higher accuracy and increased spectral and spatial resolutions of new imagers require new numerical approaches for processing imagery and separating surface and atmospheric signals. One potential approach is source separation, which allows us to determine the underlying physical causes of observed changes. Improved signal separation will allow hyperspectral instruments to better address key science questions relevant to climate change, including land-use changes, trends in clouds and atmospheric water vapor, and aerosol characteristics. In this work, we investigate a Non-negative Matrix Factorization (NMF) method for the separation of atmospheric and land surface signal sources. NMF offers marked benefits over other commonly employed techniques, including non-negativity, which avoids physically impossible results, and adaptability, which allows the method to be tailored to hyperspectral source separation. We adapt our NMF algorithm to distinguish between contributions from different physically distinct sources by introducing constraints on spectral and spatial variability and by using library spectra to inform separation. We evaluate our NMF algorithm with simulated hyperspectral images as well as hyperspectral imagery from several instruments including, the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), NASA Hyperspectral Imager for the Coastal Ocean (HICO) and National Ecological Observatory Network (NEON) Imaging Spectrometer.

Real-time demonstration hardware for enhanced DPCM video compression algorithm

NASA Technical Reports Server (NTRS)

Bizon, Thomas P.; Whyte, Wayne A., Jr.; Marcopoli, Vincent R.

1992-01-01

The lack of available wideband digital links as well as the complexity of implementation of bandwidth efficient digital video CODECs (encoder/decoder) has worked to keep the cost of digital television transmission too high to compete with analog methods. Terrestrial and satellite video service providers, however, are now recognizing the potential gains that digital video compression offers and are proposing to incorporate compression systems to increase the number of available program channels. NASA is similarly recognizing the benefits of and trend toward digital video compression techniques for transmission of high quality video from space and therefore, has developed a digital television bandwidth compression algorithm to process standard National Television Systems Committee (NTSC) composite color television signals. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a non-adaptive predictor, non-uniform quantizer and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The non-adaptive predictor and multilevel Huffman coder combine to set this technique apart from other DPCM encoding algorithms. All processing is done on a intra-field basis to prevent motion degradation and minimize hardware complexity. Computer simulations have shown the algorithm will produce broadcast quality reconstructed video at an average transmission rate of 1.8 bits/pixel. Hardware implementation of the DPCM circuit, non-adaptive predictor and non-uniform quantizer has been completed, providing realtime demonstration of the image quality at full video rates. Video sampling/reconstruction circuits have also been constructed to accomplish the analog video processing necessary for the real-time demonstration. Performance results for the completed hardware compare favorably with simulation results. Hardware implementation of the multilevel Huffman encoder/decoder is currently under development along with implementation of a buffer control algorithm to accommodate the variable data rate output of the multilevel Huffman encoder. A video CODEC of this type could be used to compress NTSC color television signals where high quality reconstruction is desirable (e.g., Space Station video transmission, transmission direct-to-the-home via direct broadcast satellite systems or cable television distribution to system headends and direct-to-the-home).

Algorithms for accelerated convergence of adaptive PCA.

PubMed

Chatterjee, C; Kang, Z; Roychowdhury, V P

2000-01-01

We derive and discuss new adaptive algorithms for principal component analysis (PCA) that are shown to converge faster than the traditional PCA algorithms due to Oja, Sanger, and Xu. It is well known that traditional PCA algorithms that are derived by using gradient descent on an objective function are slow to converge. Furthermore, the convergence of these algorithms depends on appropriate choices of the gain sequences. Since online applications demand faster convergence and an automatic selection of gains, we present new adaptive algorithms to solve these problems. We first present an unconstrained objective function, which can be minimized to obtain the principal components. We derive adaptive algorithms from this objective function by using: 1) gradient descent; 2) steepest descent; 3) conjugate direction; and 4) Newton-Raphson methods. Although gradient descent produces Xu's LMSER algorithm, the steepest descent, conjugate direction, and Newton-Raphson methods produce new adaptive algorithms for PCA. We also provide a discussion on the landscape of the objective function, and present a global convergence proof of the adaptive gradient descent PCA algorithm using stochastic approximation theory. Extensive experiments with stationary and nonstationary multidimensional Gaussian sequences show faster convergence of the new algorithms over the traditional gradient descent methods.We also compare the steepest descent adaptive algorithm with state-of-the-art methods on stationary and nonstationary sequences.

Closed Loop Guidance Trade Study for Space Launch System Block-1B Vehicle

NASA Technical Reports Server (NTRS)

Von der Porten, Paul; Ahmad, Naeem; Hawkins, Matt

2018-01-01

NASA is currently building the Space Launch System (SLS) Block-1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. The design of the next evolution of SLS, Block-1B, is well underway. The Block-1B vehicle is more capable overall than Block-1; however, the relatively low thrust-to-weight ratio of the Exploration Upper Stage (EUS) presents a challenge to the Powered Explicit Guidance (PEG) algorithm used by Block-1. To handle the long burn durations (on the order of 1000 seconds) of EUS missions, two algorithms were examined. An alternative algorithm, OPGUID, was introduced, while modifications were made to PEG. A trade study was conducted to select the guidance algorithm for future SLS vehicles. The chosen algorithm needs to support a wide variety of mission operations: ascent burns to LEO, apogee raise burns, trans-lunar injection burns, hyperbolic Earth departure burns, and contingency disposal burns using the Reaction Control System (RCS). Additionally, the algorithm must be able to respond to a single engine failure scenario. Each algorithm was scored based on pre-selected criteria, including insertion accuracy, algorithmic complexity and robustness, extensibility for potential future missions, and flight heritage. Monte Carlo analysis was used to select the final algorithm. This paper covers the design criteria, approach, and results of this trade study, showing impacts and considerations when adapting launch vehicle guidance algorithms to a broader breadth of in-space operations.

NASA's Experience with UV Remote Using SBUV and TOMS Instruments

NASA Technical Reports Server (NTRS)

Bhartia, P. K.

1999-01-01

This paper will discuss key features of the NASA algorithm that has been used to produce several highly popular geophysical products from the Solar Backscatter Ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) series of instruments. Since these instruments have a limited number of wavelengths, many innovative algorithmic approaches have been developed over the years to derive maximum information from these sensors. We will use Global Ozone Monitoring Experiment (GOME) data to test the assumptions made in these algorithms and show what additional information is contained in the GOME hyperspectral data. At NASA we are using this information to improve the SBUV and TOMS algorithms, as well as to develop more efficient algorithms to process GOME data.

NASA Acting Deputy Chief Technologist Briefed on Operation of Sonic Boom Prediction Algorithms

NASA Image and Video Library

2017-08-29

NASA Acting Deputy Chief Technologist Vicki Crips being briefed by Tim Cox, Controls Engineer at NASA’s Armstrong Flight Research Center at Edwards, California, on the operation of the sonic boom prediction algorithms being used in engineering simulation for the NASA Supersonic Quest program.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

Surface-Height Determination of Crevassed Glaciers-Mathematical Principles of an Autoadaptive Density-Dimension Algorithm and Validation Using ICESat-2 Simulator (SIMPL) Data

NASA Technical Reports Server (NTRS)

Herzfeld, Ute C.; Trantow, Thomas M.; Harding, David; Dabney, Philip W.

2017-01-01

Glacial acceleration is a main source of uncertainty in sea-level-change assessment. Measurement of ice-surface heights with a spatial and temporal resolution that not only allows elevation-change calculation, but also captures ice-surface morphology and its changes is required to aid in investigations of the geophysical processes associated with glacial acceleration.The Advanced Topographic Laser Altimeter System aboard NASAs future ICESat-2 Mission (launch 2017) will implement multibeam micropulse photon-counting lidar altimetry aimed at measuring ice-surface heights at 0.7-m along-track spacing. The instrument is designed to resolve spatial and temporal variability of rapidly changing glaciers and ice sheets and the Arctic sea ice. The new technology requires the development of a new mathematical algorithm for the retrieval of height information.We introduce the density-dimension algorithm (DDA) that utilizes the radial basis function to calculate a weighted density as a form of data aggregation in the photon cloud and considers density an additional dimension as an aid in auto-adaptive threshold determination. The auto-adaptive capability of the algorithm is necessary to separate returns from noise and signal photons under changing environmental conditions. The algorithm is evaluated using data collected with an ICESat-2 simulator instrument, the Slope Imaging Multi-polarization Photon-counting Lidar, over the heavily crevassed Giesecke Braer in Northwestern Greenland in summer 2015. Results demonstrate that ICESat-2 may be expected to provide ice-surface height measurements over crevassed glaciers and other complex ice surfaces. The DDA is generally applicable for the analysis of airborne and spaceborne micropulse photon-counting lidar data over complex and simple surfaces.

Advanced Transport Delay Compensation Algorithms: Results of Delay Measurement and Piloted Performance Tests

NASA Technical Reports Server (NTRS)

Guo, Liwen; Cardullo, Frank M.; Kelly, Lon C.

2007-01-01

This report summarizes the results of delay measurement and piloted performance tests that were conducted to assess the effectiveness of the adaptive compensator and the state space compensator for alleviating the phase distortion of transport delay in the visual system in the VMS at the NASA Langley Research Center. Piloted simulation tests were conducted to assess the effectiveness of two novel compensators in comparison to the McFarland predictor and the baseline system with no compensation. Thirteen pilots with heterogeneous flight experience executed straight-in and offset approaches, at various delay configurations, on a flight simulator where different predictors were applied to compensate for transport delay. The glideslope and touchdown errors, power spectral density of the pilot control inputs, NASA Task Load Index, and Cooper-Harper rating of the handling qualities were employed for the analyses. The overall analyses show that the adaptive predictor results in slightly poorer compensation for short added delay (up to 48 ms) and better compensation for long added delay (up to 192 ms) than the McFarland compensator. The analyses also show that the state space predictor is fairly superior for short delay and significantly superior for long delay than the McFarland compensator.

Real-Time Global Nonlinear Aerodynamic Modeling for Learn-To-Fly

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2016-01-01

Flight testing and modeling techniques were developed to accurately identify global nonlinear aerodynamic models for aircraft in real time. The techniques were developed and demonstrated during flight testing of a remotely-piloted subscale propeller-driven fixed-wing aircraft using flight test maneuvers designed to simulate a Learn-To-Fly scenario. Prediction testing was used to evaluate the quality of the global models identified in real time. The real-time global nonlinear aerodynamic modeling algorithm will be integrated and further tested with learning adaptive control and guidance for NASA Learn-To-Fly concept flight demonstrations.

Image Analysis via Fuzzy-Reasoning Approach: Prototype Applications at NASA

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steven J.

2004-01-01

A set of imaging techniques based on Fuzzy Reasoning (FR) approach was built for NASA at Kennedy Space Center (KSC) to perform complex real-time visual-related safety prototype tasks, such as detection and tracking of moving Foreign Objects Debris (FOD) during the NASA Space Shuttle liftoff and visual anomaly detection on slidewires used in the emergency egress system for Space Shuttle at the launch pad. The system has also proved its prospective in enhancing X-ray images used to screen hard-covered items leading to a better visualization. The system capability was used as well during the imaging analysis of the Space Shuttle Columbia accident. These FR-based imaging techniques include novel proprietary adaptive image segmentation, image edge extraction, and image enhancement. Probabilistic Neural Network (PNN) scheme available from NeuroShell(TM) Classifier and optimized via Genetic Algorithm (GA) was also used along with this set of novel imaging techniques to add powerful learning and image classification capabilities. Prototype applications built using these techniques have received NASA Space Awards, including a Board Action Award, and are currently being filed for patents by NASA; they are being offered for commercialization through the Research Triangle Institute (RTI), an internationally recognized corporation in scientific research and technology development. Companies from different fields, including security, medical, text digitalization, and aerospace, are currently in the process of licensing these technologies from NASA.

Cognitive Nonlinear Radar

DTIC Science & Technology

2013-01-01

intelligently selecting waveform parameters using adaptive algorithms. The adaptive algorithms optimize the waveform parameters based on (1) the EM...the environment. 15. SUBJECT TERMS cognitive radar, adaptive sensing, spectrum sensing, multi-objective optimization, genetic algorithms, machine...detection and classification block diagram. .........................................................6 Figure 5. Genetic algorithm block diagram

NASA airborne radar wind shear detection algorithm and the detection of wet microbursts in the vicinity of Orlando, Florida

NASA Technical Reports Server (NTRS)

Britt, Charles L.; Bracalente, Emedio M.

1992-01-01

The algorithms used in the NASA experimental wind shear radar system for detection, characterization, and determination of windshear hazard are discussed. The performance of the algorithms in the detection of wet microbursts near Orlando is presented. Various suggested algorithms that are currently being evaluated using the flight test results from Denver and Orlando are reviewed.

Extratropical Cyclone

Atmospheric Science Data Center

2013-04-16

... using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

Simulation for noise cancellation using LMS adaptive filter

NASA Astrophysics Data System (ADS)

Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

2017-06-01

In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

Performance seeking control excitation mode

NASA Technical Reports Server (NTRS)

Schkolnik, Gerard

1995-01-01

Flight testing of the performance seeking control (PSC) excitation mode was successfully completed at NASA Dryden on the F-15 highly integrated digital electronic control (HIDEC) aircraft. Although the excitation mode was not one of the original objectives of the PSC program, it was rapidly prototyped and implemented into the architecture of the PSC algorithm, allowing valuable and timely research data to be gathered. The primary flight test objective was to investigate the feasibility of a future measurement-based performance optimization algorithm. This future algorithm, called AdAPT, which stands for adaptive aircraft performance technology, generates and applies excitation inputs to selected control effectors. Fourier transformations are used to convert measured response and control effector data into frequency domain models which are mapped into state space models using multiterm frequency matching. Formal optimization principles are applied to produce an integrated, performance optimal effector suite. The key technical challenge of the measurement-based approach is the identification of the gradient of the performance index to the selected control effector. This concern was addressed by the excitation mode flight test. The AdAPT feasibility study utilized the PSC excitation mode to apply separate sinusoidal excitation trims to the controls - one aircraft, inlet first ramp (cowl), and one engine, throat area. Aircraft control and response data were recorded using on-board instrumentation and analyzed post-flight. Sensor noise characteristics, axial acceleration performance gradients, and repeatability were determined. Results were compared to pilot comments to assess the ride quality. Flight test results indicate that performance gradients were identified at all flight conditions, sensor noise levels were acceptable at the frequencies of interest, and excitations were generally not sensed by the pilot.

Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms.

PubMed

Arts, E E A; Popa, C D; Den Broeder, A A; Donders, R; Sandoo, A; Toms, T; Rollefstad, S; Ikdahl, E; Semb, A G; Kitas, G D; Van Riel, P L C M; Fransen, J

2016-04-01

Predictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm. Data from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated. Of the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer-Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups. This study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

An adaptive replacement algorithm for paged-memory computer systems.

NASA Technical Reports Server (NTRS)

Thorington, J. M., Jr.; Irwin, J. D.

1972-01-01

A general class of adaptive replacement schemes for use in paged memories is developed. One such algorithm, called SIM, is simulated using a probability model that generates memory traces, and the results of the simulation of this adaptive scheme are compared with those obtained using the best nonlookahead algorithms. A technique for implementing this type of adaptive replacement algorithm with state of the art digital hardware is also presented.

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

PubMed Central

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-12-19

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

Feasibility of using the Massively Parallel Processor for large eddy simulations and other Computational Fluid Dynamics applications

NASA Technical Reports Server (NTRS)

Bruno, John

1984-01-01

The results of an investigation into the feasibility of using the MPP for direct and large eddy simulations of the Navier-Stokes equations is presented. A major part of this study was devoted to the implementation of two of the standard numerical algorithms for CFD. These implementations were not run on the Massively Parallel Processor (MPP) since the machine delivered to NASA Goddard does not have sufficient capacity. Instead, a detailed implementation plan was designed and from these were derived estimates of the time and space requirements of the algorithms on a suitably configured MPP. In addition, other issues related to the practical implementation of these algorithms on an MPP-like architecture were considered; namely, adaptive grid generation, zonal boundary conditions, the table lookup problem, and the software interface. Performance estimates show that the architectural components of the MPP, the Staging Memory and the Array Unit, appear to be well suited to the numerical algorithms of CFD. This combined with the prospect of building a faster and larger MMP-like machine holds the promise of achieving sustained gigaflop rates that are required for the numerical simulations in CFD.

Higher Harmonic Control for Tiltrotor Vibration Reduction

NASA Technical Reports Server (NTRS)

Nixon, Mark W.; Kvaternik, Raymond G.; Settle, T. Ben

1997-01-01

The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of higher harmonic control (HHC) for reducing vibrations in tiltrotor aircraft operating in the airplane mode of flight, and to evaluate the effectiveness of a Bell-developed HHC algorithm called MAVSS (Multipoint Adaptive Vibration Suppression System) are presented. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5- scale semispan aeroelastic model of the V-22 which was modified to incorporate an HHC system employing both the rotor swashplate and the wing flaperon. The effectiveness of the swashplate and the flaperon acting either singly or in combination in reducing 1P and 3P wing vibrations over a wide range of tunnel airspeeds and rotor rotational speeds was demonstrated. The MAVSS algorithm was found to be robust to variations in tunnel airspeed and rotor speed, requiring only occasion-al on-line recalculations of the system transfer matrix.

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje; Stepanyan, Vahram; Barlow, Jonathan; Hardy, Gordon; Dorais, Greg; Poolla, Chaitanya; Reardon, Scott; Soloway, Donald

2014-01-01

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

Quality Assessment of Collection 6 MODIS Atmospheric Science Products

NASA Astrophysics Data System (ADS)

Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.

2015-12-01

Since the launch of the NASA Terra and Aqua satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (MODIS Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA MODIS science team investigators. MODAPS completed Collection 6 reprocessing of MODIS Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the MODIS Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of MODIS operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the recently processed C6 products. We will also describe the various tools and approaches developed to verify and assess the algorithm changes implemented by the science team to address known issues in the products and improve the quality of the products.

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

NASA Technical Reports Server (NTRS)

Butler, James; Gleason, James; Jedlovec, Gary; Coronado, Patrick

2015-01-01

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

NASA Technical Reports Server (NTRS)

1999-01-01

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

Application of higher harmonic blade feathering for helicopter vibration reduction

NASA Technical Reports Server (NTRS)

Powers, R. W.

1978-01-01

Higher harmonic blade feathering for helicopter vibration reduction is considered. Recent wind tunnel tests confirmed the effectiveness of higher harmonic control in reducing articulated rotor vibratory hub loads. Several predictive analyses developed in support of the NASA program were shown to be capable of calculating single harmonic control inputs required to minimize a single 4P hub response. In addition, a multiple-input, multiple-output harmonic control predictive analysis was developed. All techniques developed thus far obtain a solution by extracting empirical transfer functions from sampled data. Algorithm data sampling and processing requirements are minimal to encourage adaptive control system application of such techniques in a flight environment.

Multi-element array signal reconstruction with adaptive least-squares algorithms

NASA Technical Reports Server (NTRS)

Kumar, R.

1992-01-01

Two versions of the adaptive least-squares algorithm are presented for combining signals from multiple feeds placed in the focal plane of a mechanical antenna whose reflector surface is distorted due to various deformations. Coherent signal combining techniques based on the adaptive least-squares algorithm are examined for nearly optimally and adaptively combining the outputs of the feeds. The performance of the two versions is evaluated by simulations. It is demonstrated for the example considered that both of the adaptive least-squares algorithms are capable of offsetting most of the loss in the antenna gain incurred due to reflector surface deformations.

A View from Above Without Leaving the Ground

NASA Technical Reports Server (NTRS)

2004-01-01

In order to deliver accurate geospatial data and imagery to the remote sensing community, NASA is constantly developing new image-processing algorithms while refining existing ones for technical improvement. For 8 years, the NASA Regional Applications Center at Florida International University has served as a test bed for implementing and validating many of these algorithms, helping the Space Program to fulfill its strategic and educational goals in the area of remote sensing. The algorithms in return have helped the NASA Regional Applications Center develop comprehensive semantic database systems for data management, as well as new tools for disseminating geospatial information via the Internet.

Neural Networks for Flight Control

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1996-01-01

Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Seasonal comparisons of sea ice concentration estimates derived from SSM/I, OKEAN, and RADARSAT data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2002-01-01

The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea ice and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea ice concentration. To evaluate these differences, we compared SSM/I estimates of sea ice coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. Ice concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I ice concentrations were derived at National Snow and Ice Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT ice concentrations were calculated and compared. Overall, total sea ice concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D.<9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap concentrations were no more than 3.1% (S.D.<5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total ice concentrations than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total ice concentrations than the NASA Team algorithm. Total ice concentrations derived from OKEAN-01 and SSM/I satellite imagery were highly correlated during winter, spring, and fall, with mean differences of less than 8.1% (S.D.<15%) for the NASA Team algorithm, and less than 2.8% (S.D.<13.8%) for the Bootstrap algorithm. Respective differences between SSM/I NASA Team and SSM/I Bootstrap total concentrations were less than 5.3% (S.D.<6.9%). Monthly mean differences between SSM/I and OKEAN differed annually by less than 6%, with smaller differences primarily in winter. The NASA Team and Bootstrap algorithms underestimated the total sea ice concentrations relative to the RADARSAT ScanSAR no more than 3.0% (S.D.<9%) and 1.2% (S.D.<7.5%) during cold months, and no more than 12% and 7% during summer, respectively. ScanSAR tended to estimate higher ice concentrations for ice concentrations greater than 50%, when compared to SSM/I during all months. ScanSAR underestimated total sea ice concentration by 2% compared to the OKEAN-01 algorithm during cold months, and gave an overestimation by 2% during spring and summer months. Total NASA Team and Bootstrap sea ice concentration estimates derived from coincident SSM/I and OKEAN-01 data demonstrated mean differences of no more than 5.3% (S.D.<7%), 3.1% (S.D.<5.5%), 2.0% (S.D.<5.5%), and 7.3% (S.D.<10%) for fall, winter, spring, and summer periods, respectively. Large disagreements were observed between the OKEAN and NASA Team results in spring and summer for estimates of the first-year (FY) and multiyear (MY) age classes. The OKEAN-01 algorithm and data tended to estimate, on average, lower concentrations of young or FY ice and higher concentrations of total and MY ice for all months and seasons. Our results contribute to the growing body of documentation about the levels of disparity obtained when seasonal sea ice concentrations are estimated using various types of satellite data and algorithms.

Methodologies for Adaptive Flight Envelope Estimation and Protection

NASA Technical Reports Server (NTRS)

Tang, Liang; Roemer, Michael; Ge, Jianhua; Crassidis, Agamemnon; Prasad, J. V. R.; Belcastro, Christine

2009-01-01

This paper reports the latest development of several techniques for adaptive flight envelope estimation and protection system for aircraft under damage upset conditions. Through the integration of advanced fault detection algorithms, real-time system identification of the damage/faulted aircraft and flight envelop estimation, real-time decision support can be executed autonomously for improving damage tolerance and flight recoverability. Particularly, a bank of adaptive nonlinear fault detection and isolation estimators were developed for flight control actuator faults; a real-time system identification method was developed for assessing the dynamics and performance limitation of impaired aircraft; online learning neural networks were used to approximate selected aircraft dynamics which were then inverted to estimate command margins. As off-line training of network weights is not required, the method has the advantage of adapting to varying flight conditions and different vehicle configurations. The key benefit of the envelope estimation and protection system is that it allows the aircraft to fly close to its limit boundary by constantly updating the controller command limits during flight. The developed techniques were demonstrated on NASA s Generic Transport Model (GTM) simulation environments with simulated actuator faults. Simulation results and remarks on future work are presented.

Adaptive Algorithms for Automated Processing of Document Images

DTIC Science & Technology

2011-01-01

ABSTRACT Title of dissertation: ADAPTIVE ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES Mudit Agrawal, Doctor of Philosophy, 2011...2011 4. TITLE AND SUBTITLE Adaptive Algorithms for Automated Processing of Document Images 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES by Mudit Agrawal Dissertation submitted to the Faculty of the Graduate School of the University

Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the "Deep Blue" Aerosol Project

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Lee, J.; Bettenhausen, C.; Kim, W. V.; Smirnov, A.

2018-01-01

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue data set also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's S-NPP VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nm AOD of order ±(0.03+10%), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Ångström exponent and fine-mode AOD fraction are also well correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.

PubMed

Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu

2015-08-01

This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.

Adaptive Reception for Underwater Communications

DTIC Science & Technology

2011-06-01

Experimental results prove the effectiveness of the receiver. 14. SUBJECT TERMS Underwater acoustic communications, adaptive algorithms , Kalman filter...the update algorithm design and the value of the spatial diversity are addressed. In this research, an adaptive multichannel equalizer made up of a...for the time-varying nature of the channel is to use an Adaptive Decision Feedback Equalizer based on either the RLS or LMS algorithm . Although this

Star adaptation for two-algorithms used on serial computers

NASA Technical Reports Server (NTRS)

Howser, L. M.; Lambiotte, J. J., Jr.

1974-01-01

Two representative algorithms used on a serial computer and presently executed on the Control Data Corporation 6000 computer were adapted to execute efficiently on the Control Data STAR-100 computer. Gaussian elimination for the solution of simultaneous linear equations and the Gauss-Legendre quadrature formula for the approximation of an integral are the two algorithms discussed. A description is given of how the programs were adapted for STAR and why these adaptations were necessary to obtain an efficient STAR program. Some points to consider when adapting an algorithm for STAR are discussed. Program listings of the 6000 version coded in 6000 FORTRAN, the adapted STAR version coded in 6000 FORTRAN, and the STAR version coded in STAR FORTRAN are presented in the appendices.

SMI adaptive antenna arrays for weak interfering signals

NASA Technical Reports Server (NTRS)

Gupta, I. J.

1987-01-01

The performance of adaptive antenna arrays is studied when a sample matrix inversion (SMI) algorithm is used to control array weights. It is shown that conventional SMI adaptive antennas, like other adaptive antennas, are unable to suppress weak interfering signals (below thermal noise) encountered in broadcasting satellite communication systems. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is modified such that the effect of thermal noise on the weights of the adaptive array is reduced. Thus, the weights are dictated by relatively weak coherent signals. It is shown that the modified algorithm provides the desired interference protection. The use of defocused feeds as auxiliary elements of an SMI adaptive array is also discussed.

Freeing Space for NASA: Incorporating a Lossless Compression Algorithm into NASA's FOSS System

NASA Technical Reports Server (NTRS)

Fiechtner, Kaitlyn; Parker, Allen

2011-01-01

NASA's Fiber Optic Strain Sensing (FOSS) system can gather and store up to 1,536,000 bytes (1.46 megabytes) per second. Since the FOSS system typically acquires hours - or even days - of data, the system can gather hundreds of gigabytes of data for a given test event. To store such large quantities of data more effectively, NASA is modifying a Lempel-Ziv-Oberhumer (LZO) lossless data compression program to compress data as it is being acquired in real time. After proving that the algorithm is capable of compressing the data from the FOSS system, the LZO program will be modified and incorporated into the FOSS system. Implementing an LZO compression algorithm will instantly free up memory space without compromising any data obtained. With the availability of memory space, the FOSS system can be used more efficiently on test specimens, such as Unmanned Aerial Vehicles (UAVs) that can be in flight for days. By integrating the compression algorithm, the FOSS system can continue gathering data, even on longer flights.

Runway Safety Monitor Algorithm for Runway Incursion Detection and Alerting

NASA Technical Reports Server (NTRS)

Green, David F., Jr.; Jones, Denise R. (Technical Monitor)

2002-01-01

The Runway Safety Monitor (RSM) is an algorithm for runway incursion detection and alerting that was developed in support of NASA's Runway Incursion Prevention System (RIPS) research conducted under the NASA Aviation Safety Program's Synthetic Vision System element. The RSM algorithm provides pilots with enhanced situational awareness and warnings of runway incursions in sufficient time to take evasive action and avoid accidents during landings, takeoffs, or taxiing on the runway. The RSM currently runs as a component of the NASA Integrated Display System, an experimental avionics software system for terminal area and surface operations. However, the RSM algorithm can be implemented as a separate program to run on any aircraft with traffic data link capability. The report documents the RSM software and describes in detail how RSM performs runway incursion detection and alerting functions for NASA RIPS. The report also describes the RIPS flight tests conducted at the Dallas-Ft Worth International Airport (DFW) during September and October of 2000, and the RSM performance results and lessons learned from those flight tests.

Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

NASA Technical Reports Server (NTRS)

Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.

2013-01-01

The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center

Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

1999-01-01

A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

GPU Lossless Hyperspectral Data Compression System for Space Applications

NASA Technical Reports Server (NTRS)

Keymeulen, Didier; Aranki, Nazeeh; Hopson, Ben; Kiely, Aaron; Klimesh, Matthew; Benkrid, Khaled

2012-01-01

On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. At JPL, a novel, adaptive and predictive technique for lossless compression of hyperspectral data, named the Fast Lossless (FL) algorithm, was recently developed. This technique uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. Because of its outstanding performance and suitability for real-time onboard hardware implementation, the FL compressor is being formalized as the emerging CCSDS Standard for Lossless Multispectral & Hyperspectral image compression. The FL compressor is well-suited for parallel hardware implementation. A GPU hardware implementation was developed for FL targeting the current state-of-the-art GPUs from NVIDIA(Trademark). The GPU implementation on a NVIDIA(Trademark) GeForce(Trademark) GTX 580 achieves a throughput performance of 583.08 Mbits/sec (44.85 MSamples/sec) and an acceleration of at least 6 times a software implementation running on a 3.47 GHz single core Intel(Trademark) Xeon(Trademark) processor. This paper describes the design and implementation of the FL algorithm on the GPU. The massively parallel implementation will provide in the future a fast and practical real-time solution for airborne and space applications.

Classification of adaptive memetic algorithms: a comparative study.

PubMed

Ong, Yew-Soon; Lim, Meng-Hiot; Zhu, Ning; Wong, Kok-Wai

2006-02-01

Adaptation of parameters and operators represents one of the recent most important and promising areas of research in evolutionary computations; it is a form of designing self-configuring algorithms that acclimatize to suit the problem in hand. Here, our interests are on a recent breed of hybrid evolutionary algorithms typically known as adaptive memetic algorithms (MAs). One unique feature of adaptive MAs is the choice of local search methods or memes and recent studies have shown that this choice significantly affects the performances of problem searches. In this paper, we present a classification of memes adaptation in adaptive MAs on the basis of the mechanism used and the level of historical knowledge on the memes employed. Then the asymptotic convergence properties of the adaptive MAs considered are analyzed according to the classification. Subsequently, empirical studies on representatives of adaptive MAs for different type-level meme adaptations using continuous benchmark problems indicate that global-level adaptive MAs exhibit better search performances. Finally we conclude with some promising research directions in the area.

Onboard Nonlinear Engine Sensor and Component Fault Diagnosis and Isolation Scheme

NASA Technical Reports Server (NTRS)

Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong

2011-01-01

A method detects and isolates in-flight sensor, actuator, and component faults for advanced propulsion systems. In sharp contrast to many conventional methods, which deal with either sensor fault or component fault, but not both, this method considers sensor fault, actuator fault, and component fault under one systemic and unified framework. The proposed solution consists of two main components: a bank of real-time, nonlinear adaptive fault diagnostic estimators for residual generation, and a residual evaluation module that includes adaptive thresholds and a Transferable Belief Model (TBM)-based residual evaluation scheme. By employing a nonlinear adaptive learning architecture, the developed approach is capable of directly dealing with nonlinear engine models and nonlinear faults without the need of linearization. Software modules have been developed and evaluated with the NASA C-MAPSS engine model. Several typical engine-fault modes, including a subset of sensor/actuator/components faults, were tested with a mild transient operation scenario. The simulation results demonstrated that the algorithm was able to successfully detect and isolate all simulated faults as long as the fault magnitudes were larger than the minimum detectable/isolable sizes, and no misdiagnosis occurred

NASA, Navy, and AES/York sea ice concentration comparison of SSM/I algorithms with SAR derived values

NASA Technical Reports Server (NTRS)

Jentz, R. R.; Wackerman, C. C.; Shuchman, R. A.; Onstott, R. G.; Gloersen, Per; Cavalieri, Don; Ramseier, Rene; Rubinstein, Irene; Comiso, Joey; Hollinger, James

1991-01-01

Previous research studies have focused on producing algorithms for extracting geophysical information from passive microwave data regarding ice floe size, sea ice concentration, open water lead locations, and sea ice extent. These studies have resulted in four separate algorithms for extracting these geophysical parameters. Sea ice concentration estimates generated from each of these algorithms (i.e., NASA/Team, NASA/Comiso, AES/York, and Navy) are compared to ice concentration estimates produced from coincident high-resolution synthetic aperture radar (SAR) data. The SAR concentration estimates are produced from data collected in both the Beaufort Sea and the Greenland Sea in March 1988 and March 1989, respectively. The SAR data are coincident to the passive microwave data generated by the Special Sensor Microwave/Imager (SSM/I).

Study on a low complexity adaptive modulation algorithm in OFDM-ROF system with sub-carrier grouping technology

NASA Astrophysics Data System (ADS)

Liu, Chong-xin; Liu, Bo; Zhang, Li-jia; Xin, Xiang-jun; Tian, Qing-hua; Tian, Feng; Wang, Yong-jun; Rao, Lan; Mao, Yaya; Li, Deng-ao

2018-01-01

During the last decade, the orthogonal frequency division multiplexing radio-over-fiber (OFDM-ROF) system with adaptive modulation technology is of great interest due to its capability of raising the spectral efficiency dramatically, reducing the effects of fiber link or wireless channel, and improving the communication quality. In this study, according to theoretical analysis of nonlinear distortion and frequency selective fading on the transmitted signal, a low-complexity adaptive modulation algorithm is proposed in combination with sub-carrier grouping technology. This algorithm achieves the optimal performance of the system by calculating the average combined signal-to-noise ratio of each group and dynamically adjusting the origination modulation format according to the preset threshold and user's requirements. At the same time, this algorithm takes the sub-carrier group as the smallest unit in the initial bit allocation and the subsequent bit adjustment. So, the algorithm complexity is only 1 /M (M is the number of sub-carriers in each group) of Fischer algorithm, which is much smaller than many classic adaptive modulation algorithms, such as Hughes-Hartogs algorithm, Chow algorithm, and is in line with the development direction of green and high speed communication. Simulation results show that the performance of OFDM-ROF system with the improved algorithm is much better than those without adaptive modulation, and the BER of the former achieves 10e1 to 10e2 times lower than the latter when SNR values gets larger. We can obtain that this low complexity adaptive modulation algorithm is extremely useful for the OFDM-ROF system.

G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

NASA Technical Reports Server (NTRS)

Rogers, David

1991-01-01

G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

A family of variable step-size affine projection adaptive filter algorithms using statistics of channel impulse response

NASA Astrophysics Data System (ADS)

Shams Esfand Abadi, Mohammad; AbbasZadeh Arani, Seyed Ali Asghar

2011-12-01

This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial update NLMS (VSS-SPU-NLMS), the VSS-SPU-APA, and the VSS selective regressor APA (VSS-SR-APA). In VSS-SPU adaptive algorithms the filter coefficients are partially updated which reduce the computational complexity. In VSS-SR-APA, the optimal selection of input regressors is performed during the adaptation. The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through several simulations in system identification scenario.

A Controlled Study of the Effectiveness of an Adaptive Closed-Loop Algorithm to Minimize Corticosteroid-Induced Stress Hyperglycemia in Type 1 Diabetes

PubMed Central

Youssef, Joseph El; Castle, Jessica R; Branigan, Deborah L; Massoud, Ryan G; Breen, Matthew E; Jacobs, Peter G; Bequette, B Wayne; Ward, W Kenneth

2011-01-01

To be effective in type 1 diabetes, algorithms must be able to limit hyperglycemic excursions resulting from medical and emotional stress. We tested an algorithm that estimates insulin sensitivity at regular intervals and continually adjusts gain factors of a fading memory proportional-derivative (FMPD) algorithm. In order to assess whether the algorithm could appropriately adapt and limit the degree of hyperglycemia, we administered oral hydrocortisone repeatedly to create insulin resistance. We compared this indirect adaptive proportional-derivative (APD) algorithm to the FMPD algorithm, which used fixed gain parameters. Each subject with type 1 diabetes (n = 14) was studied on two occasions, each for 33 h. The APD algorithm consistently identified a fall in insulin sensitivity after hydrocortisone. The gain factors and insulin infusion rates were appropriately increased, leading to satisfactory glycemic control after adaptation (premeal glucose on day 2, 148 ± 6 mg/dl). After sufficient time was allowed for adaptation, the late postprandial glucose increment was significantly lower than when measured shortly after the onset of the steroid effect. In addition, during the controlled comparison, glycemia was significantly lower with the APD algorithm than with the FMPD algorithm. No increase in hypoglycemic frequency was found in the APD-only arm. An afferent system of duplicate amperometric sensors demonstrated a high degree of accuracy; the mean absolute relative difference of the sensor used to control the algorithm was 9.6 ± 0.5%. We conclude that an adaptive algorithm that frequently estimates insulin sensitivity and adjusts gain factors is capable of minimizing corticosteroid-induced stress hyperglycemia. PMID:22226248

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

Laidlaw, R.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Bormann, K.; Brodzik, M. J.; Burgess, A. B.; Rittger, K.; Goodale, C. E.; Joyce, M.; McGibbney, L. J.; Zimdars, P.

2014-12-01

NASA JPL's Snow Data System has a data-processing pipeline powered by Apache OODT, an open source software tool. The pipeline has been running for several years and has successfully generated a significant amount of cryosphere data, including MODIS-based products such as MODSCAG, MODDRFS and MODICE, with historical and near-real time windows and covering regions such as the Artic, Western US, Alaska, Central Europe, Asia, South America, Australia and New Zealand. The team continues to improve the pipeline, using monitoring tools such as Ganglia to give an overview of operations, and improving fault-tolerance with automated recovery scripts. Several alternative adaptations of the Snow Covered Area and Grain size (SCAG) algorithm are being investigated. These include using VIIRS and Landsat TM/ETM+ satellite data as inputs. Parallel computing techniques are being considered for core SCAG processing, such as using the PyCUDA Python API to utilize multi-core GPU architectures. An experimental version of MODSCAG is also being developed for the Google Earth Engine platform, a cloud-based service.

SMI adaptive antenna arrays for weak interfering signals. [Sample Matrix Inversion

NASA Technical Reports Server (NTRS)

Gupta, Inder J.

1986-01-01

The performance of adaptive antenna arrays in the presence of weak interfering signals (below thermal noise) is studied. It is shown that a conventional adaptive antenna array sample matrix inversion (SMI) algorithm is unable to suppress such interfering signals. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is redefined such that the effect of thermal noise on the weights of adaptive arrays is reduced. Thus, the weights are dictated by relatively weak signals. It is shown that the modified algorithm provides the desired interference protection.

Cross counter-based adaptive assembly scheme in optical burst switching networks

NASA Astrophysics Data System (ADS)

Zhu, Zhi-jun; Dong, Wen; Le, Zi-chun; Chen, Wan-jun; Sun, Xingshu

2009-11-01

A novel adaptive assembly algorithm called Cross-counter Balance Adaptive Assembly Period (CBAAP) is proposed in this paper. The major difference between CBAAP and other adaptive assembly algorithms is that the threshold of CBAAP can be dynamically adjusted according to the cross counter and step length value. In terms of assembly period and the burst loss probability, we compare the performance of CBAAP with those of three typical algorithms FAP (Fixed Assembly Period), FBL (Fixed Burst Length) and MBMAP (Min-Burst length-Max-Assembly-Period) in the simulation part. The simulation results demonstrate the effectiveness of our algorithm.

Intermediate view reconstruction using adaptive disparity search algorithm for real-time 3D processing

NASA Astrophysics Data System (ADS)

Bae, Kyung-hoon; Park, Changhan; Kim, Eun-soo

2008-03-01

In this paper, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (ASDA) is for realtime 3-dimensional (3D) processing proposed. The proposed algorithm can reduce processing time of disparity estimation by selecting adaptive disparity search range. Also, the proposed algorithm can increase the quality of the 3D imaging. That is, by adaptively predicting the mutual correlation between stereo images pair using the proposed algorithm, the bandwidth of stereo input images pair can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and disparity vectors. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm improves the PSNRs of a reconstructed image to about 4.8 dB by comparing with that of conventional algorithms, and reduces the Synthesizing time of a reconstructed image to about 7.02 sec by comparing with that of conventional algorithms.

Statistical efficiency of adaptive algorithms.

PubMed

Widrow, Bernard; Kamenetsky, Max

2003-01-01

The statistical efficiency of a learning algorithm applied to the adaptation of a given set of variable weights is defined as the ratio of the quality of the converged solution to the amount of data used in training the weights. Statistical efficiency is computed by averaging over an ensemble of learning experiences. A high quality solution is very close to optimal, while a low quality solution corresponds to noisy weights and less than optimal performance. In this work, two gradient descent adaptive algorithms are compared, the LMS algorithm and the LMS/Newton algorithm. LMS is simple and practical, and is used in many applications worldwide. LMS/Newton is based on Newton's method and the LMS algorithm. LMS/Newton is optimal in the least squares sense. It maximizes the quality of its adaptive solution while minimizing the use of training data. Many least squares adaptive algorithms have been devised over the years, but no other least squares algorithm can give better performance, on average, than LMS/Newton. LMS is easily implemented, but LMS/Newton, although of great mathematical interest, cannot be implemented in most practical applications. Because of its optimality, LMS/Newton serves as a benchmark for all least squares adaptive algorithms. The performances of LMS and LMS/Newton are compared, and it is found that under many circumstances, both algorithms provide equal performance. For example, when both algorithms are tested with statistically nonstationary input signals, their average performances are equal. When adapting with stationary input signals and with random initial conditions, their respective learning times are on average equal. However, under worst-case initial conditions, the learning time of LMS can be much greater than that of LMS/Newton, and this is the principal disadvantage of the LMS algorithm. But the strong points of LMS are ease of implementation and optimal performance under important practical conditions. For these reasons, the LMS algorithm has enjoyed very widespread application. It is used in almost every modem for channel equalization and echo cancelling. Furthermore, it is related to the famous backpropagation algorithm used for training neural networks.

Flight Test of Composite Model Reference Adaptive Control (CMRAC) Augmentation Using NASA AirSTAR Infrastructure

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Gadient, ROss; Lavretsky, Eugene

2011-01-01

This paper presents flight test results of a robust linear baseline controller with and without composite adaptive control augmentation. The flight testing was conducted using the NASA Generic Transport Model as part of the Airborne Subscale Transport Aircraft Research system at NASA Langley Research Center.

Calibration and Data Retrieval Algorithms for the NASA Langley/Ames Diode Laser Hygrometer for the NASA Trace-P Mission

NASA Technical Reports Server (NTRS)

Podolske, James R.; Sachse, Glen W.; Diskin, Glenn S.; Hipskino, R. Stephen (Technical Monitor)

2002-01-01

This paper describes the procedures and algorithms for the laboratory calibration and the field data retrieval of the NASA Langley / Ames Diode Laser Hygrometer as implemented during the NASA Trace-P mission during February to April 2000. The calibration is based on a NIST traceable dewpoint hygrometer using relatively high humidity and short pathlength. Two water lines of widely different strengths are used to increase the dynamic range of the instrument in the course of a flight. The laboratory results are incorporated into a numerical model of the second harmonic spectrum for each of the two spectral window regions using spectroscopic parameters from the HITRAN database and other sources, allowing water vapor retrieval at upper tropospheric and lower stratospheric temperatures and humidity levels. The data retrieval algorithm is simple, numerically stable, and accurate. A comparison with other water vapor instruments on board the NASA DC-8 and ER-2 aircraft is presented.

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Orr, Jeb S.; Wall, John H.; Gilligan, Eric T.

2014-01-01

This paper summarizes the Adaptive Augmenting Control (AAC) flight characterization experiments performed using an F/A-18 (TN 853). AAC was designed and developed specifically for launch vehicles, and is currently part of the baseline autopilot design for NASA's Space Launch System (SLS). The scope covered here includes a brief overview of the algorithm (covered in more detail elsewhere), motivation and benefits of flight testing, top-level SLS flight test objectives, applicability of the F/A-18 as a platform for testing a launch vehicle control design, test cases designed to fully vet the AAC algorithm, flight test results, and conclusions regarding the functionality of AAC. The AAC algorithm developed at Marshall Space Flight Center is a forward loop gain multiplicative adaptive algorithm that modifies the total attitude control system gain in response to sensed model errors or undesirable parasitic mode resonances. The AAC algorithm provides the capability to improve or decrease performance by balancing attitude tracking with the mitigation of parasitic dynamics, such as control-structure interaction or servo-actuator limit cycles. In the case of the latter, if unmodeled or mismodeled parasitic dynamics are present that would otherwise result in a closed-loop instability or near instability, the adaptive controller decreases the total loop gain to reduce the interaction between these dynamics and the controller. This is in contrast to traditional adaptive control logic, which focuses on improving performance by increasing gain. The computationally simple AAC attitude control algorithm has stability properties that are reconcilable in the context of classical frequency-domain criteria (i.e., gain and phase margin). The algorithm assumes that the baseline attitude control design is well-tuned for a nominal trajectory and is designed to adapt only when necessary. Furthermore, the adaptation is attracted to the nominal design and adapts only on an as-needed basis (see Figure 1). The MSFC algorithm design was formulated during the Constellation Program and reached a high maturity level during SLS through simulation-based development and internal and external analytical review. The AAC algorithm design has three summary-level objectives: (1) "Do no harm;" return to baseline control design when not needed, (2) Increase performance; respond to error in ability of vehicle to track command, and (3) Regain stability; respond to undesirable control-structure interaction or other parasitic dynamics. AAC has been successfully implemented as part of the Space Launch System baseline design, including extensive testing in high-fidelity 6-DOF simulations the details of which are described in [1]. The Dryden Flight Research Center's F/A-18 Full-Scale Advanced Systems Testbed (FAST) platform is used to conduct an algorithm flight characterization experiment intended to fully vet the aforementioned design objectives. FAST was specifically designed with this type of test program in mind. The onboard flight control system has full-authority experiment control of ten aerodynamic effectors and two throttles. It has production and research sensor inputs and pilot engage/disengage and real-time configuration of up to eight different experiments on a single flight. It has failure detection and automatic reversion to fail-safe mode. The F/A-18 aircraft has an experiment envelope cleared for full-authority control and maneuvering and exhibits characteristics for robust recovery from unusual attitudes and configurations aided by the presence of a qualified test pilot. The F/A-18 aircraft has relatively high mass and inertia with exceptional performance; the F/A-18 also has a large thrust-to-weight ratio, owing to its military heritage. This enables the simulation of a portion of the ascent trajectory with a high degree of dynamic similarity to a launch vehicle, and the research flight control system can simulate unstable longitudinal dynamics. Parasitic dynamics such as slosh and bending modes, as well as atmospheric disturbances, are being produced by the airframe via modification of bending filters and the use of secondary control surfaces, including leading and trailing edge flaps, symmetric ailerons, and symmetric rudders. The platform also has the ability to inject signals in flight to simulate structural mode resonances or other challenging dynamics. This platform also offers more test maneuvers and longer maneuver times than a single rocket or missile test, which provides ample opportunity to fully and repeatedly exercise all aspects of the algorithm. Prior to testing on an F/A-18, AAC was the only component of the SLS autopilot design that had not been flight tested. The testing described in this paper raises the Technology Readiness Level (TRL) early in the SLS Program and is able to demonstrate its capabilities and robustness in a flight environment.

Adaptive optics image restoration algorithm based on wavefront reconstruction and adaptive total variation method

NASA Astrophysics Data System (ADS)

Li, Dongming; Zhang, Lijuan; Wang, Ting; Liu, Huan; Yang, Jinhua; Chen, Guifen

2016-11-01

To improve the adaptive optics (AO) image's quality, we study the AO image restoration algorithm based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF). Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution issue. The image restoration experiments are performed to verify the image restoration effect of our proposed algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44% respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is significantly improved.

Spatial and Temporal Distribution of Cloud Properties Observed by MODIS: Preliminary Level-3 Results from the Collection 5 Reprocessing

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the MODIS Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and Aqua data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and Aqua results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Simulator Evaluation of Runway Incursion Prevention Technology for General Aviation Operations

NASA Technical Reports Server (NTRS)

Jones, Denise R.; Prinzel, Lawrence J., III

2011-01-01

A Runway Incursion Prevention System (RIPS) has been designed under previous research to enhance airport surface operations situation awareness and provide cockpit alerts of potential runway conflict, during transport aircraft category operations, in order to prevent runway incidents while also improving operations capability. This study investigated an adaptation of RIPS for low-end general aviation operations using a fixed-based simulator at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). The purpose of the study was to evaluate modified RIPS aircraft-based incursion detection algorithms and associated alerting and airport surface display concepts for low-end general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Low complexity adaptive equalizers for underwater acoustic communications

NASA Astrophysics Data System (ADS)

Soflaei, Masoumeh; Azmi, Paeiz

2014-08-01

Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggested ways is to use adaptive equalizers. Convergence rate and misadjustment error in adaptive algorithms play important roles in adaptive equalizer performance. In this paper, affine projection algorithm (APA), selective regressor APA(SR-APA), family of selective partial update (SPU) algorithms, family of set-membership (SM) algorithms and selective partial update selective regressor APA (SPU-SR-APA) are compared with conventional algorithms such as the least mean square (LMS) in underwater acoustic communications. We apply experimental data from the Strait of Hormuz for demonstrating the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error (MSE) of SR-APA, SPU-APA, SPU-normalized least mean square (SPU-NLMS), SPU-SR-APA, SM-APA and SM-NLMS algorithms decrease in comparison with the LMS algorithm. Also these algorithms have better convergence rates than LMS type algorithm.

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Zheng, E-mail: 19994035@sina.com; Wang, Jun; Zhou, Bihua

2014-03-15

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented tomore » tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.« less

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Interior Noise Reduction by Adaptive Feedback Vibration Control

NASA Technical Reports Server (NTRS)

Lim, Tae W.

1998-01-01

The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study. The on-line identification algorithm developed in this research will be useful in constructing a state estimator for feedback vibration control.

Motion Cueing Algorithm Development: New Motion Cueing Program Implementation and Tuning

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.

2005-01-01

A computer program has been developed for the purpose of driving the NASA Langley Research Center Visual Motion Simulator (VMS). This program includes two new motion cueing algorithms, the optimal algorithm and the nonlinear algorithm. A general description of the program is given along with a description and flowcharts for each cueing algorithm, and also descriptions and flowcharts for subroutines used with the algorithms. Common block variable listings and a program listing are also provided. The new cueing algorithms have a nonlinear gain algorithm implemented that scales each aircraft degree-of-freedom input with a third-order polynomial. A description of the nonlinear gain algorithm is given along with past tuning experience and procedures for tuning the gain coefficient sets for each degree-of-freedom to produce the desired piloted performance. This algorithm tuning will be needed when the nonlinear motion cueing algorithm is implemented on a new motion system in the Cockpit Motion Facility (CMF) at the NASA Langley Research Center.

Wideband RELAX and wideband CLEAN for aeroacoustic imaging

NASA Astrophysics Data System (ADS)

Wang, Yanwei; Li, Jian; Stoica, Petre; Sheplak, Mark; Nishida, Toshikazu

2004-02-01

Microphone arrays can be used for acoustic source localization and characterization in wind tunnel testing. In this paper, the wideband RELAX (WB-RELAX) and the wideband CLEAN (WB-CLEAN) algorithms are presented for aeroacoustic imaging using an acoustic array. WB-RELAX is a parametric approach that can be used efficiently for point source imaging without the sidelobe problems suffered by the delay-and-sum beamforming approaches. WB-CLEAN does not have sidelobe problems either, but it behaves more like a nonparametric approach and can be used for both point source and distributed source imaging. Moreover, neither of the algorithms suffers from the severe performance degradations encountered by the adaptive beamforming methods when the number of snapshots is small and/or the sources are highly correlated or coherent with each other. A two-step optimization procedure is used to implement the WB-RELAX and WB-CLEAN algorithms efficiently. The performance of WB-RELAX and WB-CLEAN is demonstrated by applying them to measured data obtained at the NASA Langley Quiet Flow Facility using a small aperture directional array (SADA). Somewhat surprisingly, using these approaches, not only were the parameters of the dominant source accurately determined, but a highly correlated multipath of the dominant source was also discovered.

Identification of the focal plane wavefront control system using E-M algorithm

NASA Astrophysics Data System (ADS)

Sun, He; Kasdin, N. Jeremy; Vanderbei, Robert

2017-09-01

In a typical focal plane wavefront control (FPWC) system, such as the adaptive optics system of NASA's WFIRST mission, the efficient controllers and estimators in use are usually model-based. As a result, the modeling accuracy of the system influences the ultimate performance of the control and estimation. Currently, a linear state space model is used and calculated based on lab measurements using Fourier optics. Although the physical model is clearly defined, it is usually biased due to incorrect distance measurements, imperfect diagnoses of the optical aberrations, and our lack of knowledge of the deformable mirrors (actuator gains and influence functions). In this paper, we present a new approach for measuring/estimating the linear state space model of a FPWC system using the expectation-maximization (E-M) algorithm. Simulation and lab results in the Princeton's High Contrast Imaging Lab (HCIL) show that the E-M algorithm can well handle both the amplitude and phase errors and accurately recover the system. Using the recovered state space model, the controller creates dark holes with faster speed. The final accuracy of the model depends on the amount of data used for learning.

Identification of integrated airframe: Propulsion effects on an F-15 aircraft for application to drag minimization

NASA Technical Reports Server (NTRS)

Schkolnik, Gerard S.

1993-01-01

The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.

Identification of integrated airframe-propulsion effects on an F-15 aircraft for application to drag minimization

NASA Technical Reports Server (NTRS)

Schkolnik, Gerald S.

1993-01-01

The application of an adaptive real-time measurement-based performance optimization technique is being explored for a future flight research program. The key technical challenge of the approach is parameter identification, which uses a perturbation-search technique to identify changes in performance caused by forced oscillations of the controls. The controls on the NASA F-15 highly integrated digital electronic control (HIDEC) aircraft were perturbed using inlet cowl rotation steps at various subsonic and supersonic flight conditions to determine the effect on aircraft performance. The feasibility of the perturbation-search technique for identifying integrated airframe-propulsion system performance effects was successfully shown through flight experiments and postflight data analysis. Aircraft response and control data were analyzed postflight to identify gradients and to determine the minimum drag point. Changes in longitudinal acceleration as small as 0.004 g were measured, and absolute resolution was estimated to be 0.002 g or approximately 50 lbf of drag. Two techniques for identifying performance gradients were compared: a least-squares estimation algorithm and a modified maximum likelihood estimator algorithm. A complementary filter algorithm was used with the least squares estimator.

Wideband RELAX and wideband CLEAN for aeroacoustic imaging.

PubMed

Wang, Yanwei; Li, Jian; Stoica, Petre; Sheplak, Mark; Nishida, Toshikazu

2004-02-01

Microphone arrays can be used for acoustic source localization and characterization in wind tunnel testing. In this paper, the wideband RELAX (WB-RELAX) and the wideband CLEAN (WB-CLEAN) algorithms are presented for aeroacoustic imaging using an acoustic array. WB-RELAX is a parametric approach that can be used efficiently for point source imaging without the sidelobe problems suffered by the delay-and-sum beamforming approaches. WB-CLEAN does not have sidelobe problems either, but it behaves more like a nonparametric approach and can be used for both point source and distributed source imaging. Moreover, neither of the algorithms suffers from the severe performance degradations encountered by the adaptive beamforming methods when the number of snapshots is small and/or the sources are highly correlated or coherent with each other. A two-step optimization procedure is used to implement the WB-RELAX and WB-CLEAN algorithms efficiently. The performance of WB-RELAX and WB-CLEAN is demonstrated by applying them to measured data obtained at the NASA Langley Quiet Flow Facility using a small aperture directional array (SADA). Somewhat surprisingly, using these approaches, not only were the parameters of the dominant source accurately determined, but a highly correlated multipath of the dominant source was also discovered.

Adaptive control of nonlinear system using online error minimum neural networks.

PubMed

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

A Self Adaptive Differential Evolution Algorithm for Global Optimization

NASA Astrophysics Data System (ADS)

Kumar, Pravesh; Pant, Millie

This paper presents a new Differential Evolution algorithm based on hybridization of adaptive control parameters and trigonometric mutation. First we propose a self adaptive DE named ADE where choice of control parameter F and Cr is not fixed at some constant value but is taken iteratively. The proposed algorithm is further modified by applying trigonometric mutation in it and the corresponding algorithm is named as ATDE. The performance of ATDE is evaluated on the set of 8 benchmark functions and the results are compared with the classical DE algorithm in terms of average fitness function value, number of function evaluations, convergence time and success rate. The numerical result shows the competence of the proposed algorithm.

SU-F-J-66: Anatomy Deformation Based Comparison Between One-Step and Two-Step Optimization for Online ART

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Z; Yu, G; Qin, S

Purpose: This study investigated that how the quality of adapted plan was affected by inter-fractional anatomy deformation by using one-step and two-step optimization for on line adaptive radiotherapy (ART) procedure. Methods: 10 lung carcinoma patients were chosen randomly to produce IMRT plan by one-step and two-step algorithms respectively, and the prescribed dose was set as 60 Gy on the planning target volume (PTV) for all patients. To simulate inter-fractional target deformation, four specific cases were created by systematic anatomy variation; including target superior shift 0.5 cm, 0.3cm contraction, 0.3 cm expansion and 45-degree rotation. Based on these four anatomy deformation,more » adapted plan, regenerated plan and non-adapted plan were created to evaluate quality of adaptation. Adapted plans were generated automatically by using one-step and two-step algorithms respectively to optimize original plans, and regenerated plans were manually created by experience physicists. Non-adapted plans were produced by recalculating the dose distribution based on corresponding original plans. The deviations among these three plans were statistically analyzed by paired T-test. Results: In PTV superior shift case, adapted plans had significantly better PTV coverage by using two-step algorithm compared with one-step one, and meanwhile there was a significant difference of V95 by comparison with adapted and non-adapted plans (p=0.0025). In target contraction deformation, with almost same PTV coverage, the total lung received lower dose using one-step algorithm than two-step algorithm (p=0.0143,0.0126 for V20, Dmean respectively). In other two deformation cases, there were no significant differences observed by both two optimized algorithms. Conclusion: In geometry deformation such as target contraction, with comparable PTV coverage, one-step algorithm gave better OAR sparing than two-step algorithm. Reversely, the adaptation by using two-step algorithm had higher efficiency and accuracy as target occurred position displacement. We want to thank Dr. Lei Xing and Dr. Yong Yang in the Stanford University School of Medicine for this work. This work was jointly supported by NSFC (61471226), Natural Science Foundation for Distinguished Young Scholars of Shandong Province (JQ201516), and China Postdoctoral Science Foundation (2015T80739, 2014M551949).« less

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

2017-01-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

Adaptive optics compensation of orbital angular momentum beams with a modified Gerchberg-Saxton-based phase retrieval algorithm

NASA Astrophysics Data System (ADS)

Chang, Huan; Yin, Xiao-li; Cui, Xiao-zhou; Zhang, Zhi-chao; Ma, Jian-xin; Wu, Guo-hua; Zhang, Li-jia; Xin, Xiang-jun

2017-12-01

Practical orbital angular momentum (OAM)-based free-space optical (FSO) communications commonly experience serious performance degradation and crosstalk due to atmospheric turbulence. In this paper, we propose a wave-front sensorless adaptive optics (WSAO) system with a modified Gerchberg-Saxton (GS)-based phase retrieval algorithm to correct distorted OAM beams. We use the spatial phase perturbation (SPP) GS algorithm with a distorted probe Gaussian beam as the only input. The principle and parameter selections of the algorithm are analyzed, and the performance of the algorithm is discussed. The simulation results show that the proposed adaptive optics (AO) system can significantly compensate for distorted OAM beams in single-channel or multiplexed OAM systems, which provides new insights into adaptive correction systems using OAM beams.

Improved adaptive genetic algorithm with sparsity constraint applied to thermal neutron CT reconstruction of two-phase flow

NASA Astrophysics Data System (ADS)

Yan, Mingfei; Hu, Huasi; Otake, Yoshie; Taketani, Atsushi; Wakabayashi, Yasuo; Yanagimachi, Shinzo; Wang, Sheng; Pan, Ziheng; Hu, Guang

2018-05-01

Thermal neutron computer tomography (CT) is a useful tool for visualizing two-phase flow due to its high imaging contrast and strong penetrability of neutrons for tube walls constructed with metallic material. A novel approach for two-phase flow CT reconstruction based on an improved adaptive genetic algorithm with sparsity constraint (IAGA-SC) is proposed in this paper. In the algorithm, the neighborhood mutation operator is used to ensure the continuity of the reconstructed object. The adaptive crossover probability P c and mutation probability P m are improved to help the adaptive genetic algorithm (AGA) achieve the global optimum. The reconstructed results for projection data, obtained from Monte Carlo simulation, indicate that the comprehensive performance of the IAGA-SC algorithm exceeds the adaptive steepest descent-projection onto convex sets (ASD-POCS) algorithm in restoring typical and complex flow regimes. It especially shows great advantages in restoring the simply connected flow regimes and the shape of object. In addition, the CT experiment for two-phase flow phantoms was conducted on the accelerator-driven neutron source to verify the performance of the developed IAGA-SC algorithm.

Real-Time Feedback Control of Flow-Induced Cavity Tones. Part 2; Adaptive Control

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cabell, R. H.; Cattafesta, L. N., III

2006-01-01

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. Past input-output data and an estimate of the open-loop pulse response sequence are all that is needed to implement the algorithm for application at fixed Mach numbers. Transient measurements made during controller adaptation revealed that the controller coefficients converged to a steady state in the mean, and this implies that adaptation can be turned off at some point with no degradation in control performance. When converged, the control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. However, as in the case of fixed-gain GPC, the adaptive GPC performance was limited by spillover in sidebands around the suppressed Rossiter modes. The algorithm was also able to maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Beyond this range, stable operation of the control algorithm was not possible due to the fixed plant model in the algorithm.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Adaptive Flight Control Research at NASA

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2008-01-01

A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

PubMed Central

Ahmad, Noor Atinah

2014-01-01

An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

Assessment of the State of the Art of Flight Control Technologies as Applicable to Adverse Conditions

NASA Technical Reports Server (NTRS)

Reveley, Mary s.; Briggs, Jeffrey L.; Leone, Karen M.; Kurtoglu, Tolga; Withrow, Colleen A.

2010-01-01

Literature from academia, industry, and other Government agencies was surveyed to assess the state of the art in current Integrated Resilient Aircraft Control (IRAC) aircraft technologies. Over 100 papers from 25 conferences from the time period 2004 to 2009 were reviewed. An assessment of the general state of the art in adaptive flight control is summarized first, followed by an assessment of the state of the art as applicable to 13 identified adverse conditions. Specific areas addressed in the general assessment include flight control when compensating for damage or reduced performance, retrofit software upgrades to flight controllers, flight control through engine response, and finally test and validation of new adaptive controllers. The state-of-the-art assessment applicable to the adverse conditions include technologies not specifically related to flight control, but may serve as inputs to a future flight control algorithm. This study illustrates existing gaps and opportunities for additional research by the NASA IRAC Project

Real-Time Stability and Control Derivative Extraction From F-15 Flight Data

NASA Technical Reports Server (NTRS)

Smith, Mark S.; Moes, Timothy R.; Morelli, Eugene A.

2003-01-01

A real-time, frequency-domain, equation-error parameter identification (PID) technique was used to estimate stability and control derivatives from flight data. This technique is being studied to support adaptive control system concepts currently being developed by NASA (National Aeronautics and Space Administration), academia, and industry. This report describes the basic real-time algorithm used for this study and implementation issues for onboard usage as part of an indirect-adaptive control system. A confidence measures system for automated evaluation of PID results is discussed. Results calculated using flight data from a modified F-15 aircraft are presented. Test maneuvers included pilot input doublets and automated inputs at several flight conditions. Estimated derivatives are compared to aerodynamic model predictions. Data indicate that the real-time PID used for this study performs well enough to be used for onboard parameter estimation. For suitable test inputs, the parameter estimates converged rapidly to sufficient levels of accuracy. The devised confidence measures used were moderately successful.

Pitch-Learning Algorithm For Speech Encoders

NASA Technical Reports Server (NTRS)

Bhaskar, B. R. Udaya

1988-01-01

Adaptive algorithm detects and corrects errors in sequence of estimates of pitch period of speech. Algorithm operates in conjunction with techniques used to estimate pitch period. Used in such parametric and hybrid speech coders as linear predictive coders and adaptive predictive coders.

An Adaptive Buddy Check for Observational Quality Control

NASA Technical Reports Server (NTRS)

Dee, Dick P.; Rukhovets, Leonid; Todling, Ricardo; DaSilva, Arlindo M.; Larson, Jay W.; Einaudi, Franco (Technical Monitor)

2000-01-01

An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

Adaptive Two Dimensional RLS (Recursive Least Squares) Algorithms

DTIC Science & Technology

1989-03-01

in Monterey wonderful. IX I. INTRODUCTION Adaptive algorithms have been used successfully for many years in a wide range of digital signal...SIMULATION RESULTS The 2-D FRLS algorithm was tested both on computer-generated data and on digitized images. For a baseline reference the 2-D L:rv1S...Alexander, S. T. Adaptivt Signal Processing: Theory and Applications. Springer- Verlag, New York. 1986. 7. Bellanger, Maurice G. Adaptive Digital

Multi-objective Optimization Design of Gear Reducer Based on Adaptive Genetic Algorithms

NASA Astrophysics Data System (ADS)

Li, Rui; Chang, Tian; Wang, Jianwei; Wei, Xiaopeng; Wang, Jinming

2008-11-01

An adaptive Genetic Algorithm (GA) is introduced to solve the multi-objective optimized design of the reducer. Firstly, according to the structure, strength, etc. in a reducer, a multi-objective optimized model of the helical gear reducer is established. And then an adaptive GA based on a fuzzy controller is introduced, aiming at the characteristics of multi-objective, multi-parameter, multi-constraint conditions. Finally, a numerical example is illustrated to show the advantages of this approach and the effectiveness of an adaptive genetic algorithm used in optimized design of a reducer.

Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction

NASA Technical Reports Server (NTRS)

Whitmore, S. A.

1985-01-01

The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the space shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.

Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2018-06-01

To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

Combination of Adaptive Feedback Cancellation and Binaural Adaptive Filtering in Hearing Aids

NASA Astrophysics Data System (ADS)

Lombard, Anthony; Reindl, Klaus; Kellermann, Walter

2009-12-01

We study a system combining adaptive feedback cancellation and adaptive filtering connecting inputs from both ears for signal enhancement in hearing aids. For the first time, such a binaural system is analyzed in terms of system stability, convergence of the algorithms, and possible interaction effects. As major outcomes of this study, a new stability condition adapted to the considered binaural scenario is presented, some already existing and commonly used feedback cancellation performance measures for the unilateral case are adapted to the binaural case, and possible interaction effects between the algorithms are identified. For illustration purposes, a blind source separation algorithm has been chosen as an example for adaptive binaural spatial filtering. Experimental results for binaural hearing aids confirm the theoretical findings and the validity of the new measures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marathe, Aniruddha P.; Harris, Rachel A.; Lowenthal, David K.

The use of clouds to execute high-performance computing (HPC) applications has greatly increased recently. Clouds provide several potential advantages over traditional supercomputers and in-house clusters. The most popular cloud is currently Amazon EC2, which provides fixed-cost and variable-cost, auction-based options. The auction market trades lower cost for potential interruptions that necessitate checkpointing; if the market price exceeds the bid price, a node is taken away from the user without warning. We explore techniques to maximize performance per dollar given a time constraint within which an application must complete. Specifically, we design and implement multiple techniques to reduce expected cost bymore » exploiting redundancy in the EC2 auction market. We then design an adaptive algorithm that selects a scheduling algorithm and determines the bid price. We show that our adaptive algorithm executes programs up to seven times cheaper than using the on-demand market and up to 44 percent cheaper than the best non-redundant, auction-market algorithm. We extend our adaptive algorithm to incorporate application scalability characteristics for further cost savings. In conclusion, we show that the adaptive algorithm informed with scalability characteristics of applications achieves up to 56 percent cost savings compared to the expected cost for the base adaptive algorithm run at a fixed, user-defined scale.« less

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

NASA Astrophysics Data System (ADS)

Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

NASA Astrophysics Data System (ADS)

Choi, Young Hwan; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon

2017-11-01

In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Flight Research into Simple Adaptive Control on the NASA FAST Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curtis E.

2011-01-01

A series of simple adaptive controllers with varying levels of complexity were designed, implemented and flight tested on the NASA Full-Scale Advanced Systems Testbed (FAST) aircraft. Lessons learned from the development and flight testing are presented.

System identification and model reduction using modulating function techniques

NASA Technical Reports Server (NTRS)

Shen, Yan

1993-01-01

Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

An environment-adaptive management algorithm for hearing-support devices incorporating listening situation and noise type classifiers.

PubMed

Yook, Sunhyun; Nam, Kyoung Won; Kim, Heepyung; Hong, Sung Hwa; Jang, Dong Pyo; Kim, In Young

2015-04-01

In order to provide more consistent sound intelligibility for the hearing-impaired person, regardless of environment, it is necessary to adjust the setting of the hearing-support (HS) device to accommodate various environmental circumstances. In this study, a fully automatic HS device management algorithm that can adapt to various environmental situations is proposed; it is composed of a listening-situation classifier, a noise-type classifier, an adaptive noise-reduction algorithm, and a management algorithm that can selectively turn on/off one or more of the three basic algorithms-beamforming, noise-reduction, and feedback cancellation-and can also adjust internal gains and parameters of the wide-dynamic-range compression (WDRC) and noise-reduction (NR) algorithms in accordance with variations in environmental situations. Experimental results demonstrated that the implemented algorithms can classify both listening situation and ambient noise type situations with high accuracies (92.8-96.4% and 90.9-99.4%, respectively), and the gains and parameters of the WDRC and NR algorithms were successfully adjusted according to variations in environmental situation. The average values of signal-to-noise ratio (SNR), frequency-weighted segmental SNR, Perceptual Evaluation of Speech Quality, and mean opinion test scores of 10 normal-hearing volunteers of the adaptive multiband spectral subtraction (MBSS) algorithm were improved by 1.74 dB, 2.11 dB, 0.49, and 0.68, respectively, compared to the conventional fixed-parameter MBSS algorithm. These results indicate that the proposed environment-adaptive management algorithm can be applied to HS devices to improve sound intelligibility for hearing-impaired individuals in various acoustic environments. Copyright © 2014 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Synthesis of the adaptive continuous system for the multi-axle wheeled vehicle body oscillation damping

NASA Astrophysics Data System (ADS)

Zhileykin, M. M.; Kotiev, G. O.; Nagatsev, M. V.

2018-02-01

In order to meet the growing mobility requirements for the wheeled vehicles on all types of terrain the engineers have to develop a large number of specialized control algorithms for the multi-axle wheeled vehicle (MWV) suspension improving such qualities as ride comfort, handling and stability. The authors have developed an adaptive algorithm of the dynamic damping of the MVW body oscillations. The algorithm provides high ride comfort and high mobility of the vehicle. The article discloses a method for synthesis of an adaptive dynamic continuous algorithm of the MVW body oscillation damping and provides simulation results proving high efficiency of the developed control algorithm.

Efficient Probabilistic Diagnostics for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Mengshoel, Ole J.; Chavira, Mark; Cascio, Keith; Poll, Scott; Darwiche, Adnan; Uckun, Serdar

2008-01-01

We consider in this work the probabilistic approach to model-based diagnosis when applied to electrical power systems (EPSs). Our probabilistic approach is formally well-founded, as it based on Bayesian networks and arithmetic circuits. We investigate the diagnostic task known as fault isolation, and pay special attention to meeting two of the main challenges . model development and real-time reasoning . often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-to-use speci.cation language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In essence, we introduce a high-level EPS speci.cation language from which Bayesian networks that can diagnose multiple simultaneous failures are auto-generated, and we illustrate the feasibility of using arithmetic circuits, compiled from Bayesian networks, for real-time diagnosis on real-world EPSs of interest to NASA. The experimental system is a real-world EPS, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. In experiments with the ADAPT Bayesian network, which currently contains 503 discrete nodes and 579 edges, we .nd high diagnostic accuracy in scenarios where one to three faults, both in components and sensors, were inserted. The time taken to compute the most probable explanation using arithmetic circuits has a small mean of 0.2625 milliseconds and standard deviation of 0.2028 milliseconds. In experiments with data from ADAPT we also show that arithmetic circuit evaluation substantially outperforms joint tree propagation and variable elimination, two alternative algorithms for diagnosis using Bayesian network inference.

An Active Damping at Blade Resonances Using Piezoelectric Transducers

NASA Technical Reports Server (NTRS)

Choi, Benjamin; Morrison, Carlos; Duffy, Kirsten

2008-01-01

The NASA Glenn Research Center (GRC) is developing an active damping at blade resonances using piezoelectric structure to reduce excessive vibratory stresses that lead to high cycle fatigue (HCF) failures in aircraft engine turbomachinery. Conventional passive damping work was shown first on a nonrotating beam made by Ti-6A1-4V with a pair of identical piezoelectric patches, and then active feedback control law was derived in terms of inductor, resister, and capacitor to control resonant frequency only. Passive electronic circuit components and adaptive feature could be easily programmable into control algorithm. Experimental active damping was demonstrated on two test specimens achieving significant damping on tip displacement and patch location. Also a multimode control technique was shown to control several modes.

High Speed Research Noise Prediction Code (HSRNOISE) User's and Theoretical Manual

NASA Technical Reports Server (NTRS)

Golub, Robert (Technical Monitor); Rawls, John W., Jr.; Yeager, Jessie C.

2004-01-01

This report describes a computer program, HSRNOISE, that predicts noise levels for a supersonic aircraft powered by mixed flow turbofan engines with rectangular mixer-ejector nozzles. It fully documents the noise prediction algorithms, provides instructions for executing the HSRNOISE code, and provides predicted noise levels for the High Speed Research (HSR) program Technology Concept (TC) aircraft. The component source noise prediction algorithms were developed jointly by Boeing, General Electric Aircraft Engines (GEAE), NASA and Pratt & Whitney during the course of the NASA HSR program. Modern Technologies Corporation developed an alternative mixer ejector jet noise prediction method under contract to GEAE that has also been incorporated into the HSRNOISE prediction code. Algorithms for determining propagation effects and calculating noise metrics were taken from the NASA Aircraft Noise Prediction Program.

Performance seeking control: Program overview and future directions

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Orme, John S.

1993-01-01

A flight test evaluation of the performance-seeking control (PSC) algorithm on the NASA F-15 highly integrated digital electronic control research aircraft was conducted for single-engine operation at subsonic and supersonic speeds. The model-based PSC system was developed with three optimization modes: minimum fuel flow at constant thrust, minimum turbine temperature at constant thrust, and maximum thrust at maximum dry and full afterburner throttle settings. Subsonic and supersonic flight testing were conducted at the NASA Dryden Flight Research Facility covering the three PSC optimization modes and over the full throttle range. Flight results show substantial benefits. In the maximum thrust mode, thrust increased up to 15 percent at subsonic and 10 percent at supersonic flight conditions. The minimum fan turbine inlet temperature mode reduced temperatures by more than 100 F at high altitudes. The minimum fuel flow mode results decreased fuel consumption up to 2 percent in the subsonic regime and almost 10 percent supersonically. These results demonstrate that PSC technology can benefit the next generation of fighter or transport aircraft. NASA Dryden is developing an adaptive aircraft performance technology system that is measurement based and uses feedback to ensure optimality. This program will address the technical weaknesses identified in the PSC program and will increase performance gains.

Cosmological N-body Simulation

NASA Astrophysics Data System (ADS)

Lake, George

1994-05-01

.90ex> }}} The ``N'' in N-body calculations has doubled every year for the last two decades. To continue this trend, the UW N-body group is working on algorithms for the fast evaluation of gravitational forces on parallel computers and establishing rigorous standards for the computations. In these algorithms, the computational cost per time step is ~ 10(3) pairwise forces per particle. A new adaptive time integrator enables us to perform high quality integrations that are fully temporally and spatially adaptive. SPH--smoothed particle hydrodynamics will be added to simulate the effects of dissipating gas and magnetic fields. The importance of these calculations is two-fold. First, they determine the nonlinear consequences of theories for the structure of the Universe. Second, they are essential for the interpretation of observations. Every galaxy has six coordinates of velocity and position. Observations determine two sky coordinates and a line of sight velocity that bundles universal expansion (distance) together with a random velocity created by the mass distribution. Simulations are needed to determine the underlying structure and masses. The importance of simulations has moved from ex post facto explanation to an integral part of planning large observational programs. I will show why high quality simulations with ``large N'' are essential to accomplish our scientific goals. This year, our simulations have N >~ 10(7) . This is sufficient to tackle some niche problems, but well short of our 5 year goal--simulating The Sloan Digital Sky Survey using a few Billion particles (a Teraflop-year simulation). Extrapolating past trends, we would have to ``wait'' 7 years for this hundred-fold improvement. Like past gains, significant changes in the computational methods are required for these advances. I will describe new algorithms, algorithmic hacks and a dedicated computer to perform Billion particle simulations. Finally, I will describe research that can be enabled by Petaflop computers. This research is supported by the NASA HPCC/ESS program.

Properties of an adaptive feedback equalization algorithm.

PubMed

Engebretson, A M; French-St George, M

1993-01-01

This paper describes a new approach to feedback equalization for hearing aids. The method involves the use of an adaptive algorithm that estimates and tracks the characteristic of the hearing aid feedback path. The algorithm is described and the results of simulation studies and bench testing are presented.

SIMULATION OF DISPERSION OF A POWER PLANT PLUME USING AN ADAPTIVE GRID ALGORITHM

EPA Science Inventory

A new dynamic adaptive grid algorithm has been developed for use in air quality modeling. This algorithm uses a higher order numerical scheme?the piecewise parabolic method (PPM)?for computing advective solution fields; a weight function capable of promoting grid node clustering ...

SIMULATION OF A REACTING POLLUTANT PUFF USING AN ADAPTIVE GRID ALGORITHM

EPA Science Inventory

A new dynamic solution adaptive grid algorithm DSAGA-PPM, has been developed for use in air quality modeling. In this paper, this algorithm is described and evaluated with a test problem. Cone-shaped distributions of various chemical species undergoing chemical reactions are rota...

Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization.

PubMed

Wong, Ieong; Liu, Wenjia; Ho, Chih-Ming; Ding, Xianting

2017-06-01

Differential evolution (DE) has been applied extensively in drug combination optimization studies in the past decade. It allows for identification of desired drug combinations with minimal experimental effort. This article proposes an adaptive population-sizing method for the DE algorithm. Our new method presents improvements in terms of efficiency and convergence over the original DE algorithm and constant stepwise population reduction-based DE algorithm, which would lead to a reduced number of cells and animals required to identify an optimal drug combination. The method continuously adjusts the reduction of the population size in accordance with the stage of the optimization process. Our adaptive scheme limits the population reduction to occur only at the exploitation stage. We believe that continuously adjusting for a more effective population size during the evolutionary process is the major reason for the significant improvement in the convergence speed of the DE algorithm. The performance of the method is evaluated through a set of unimodal and multimodal benchmark functions. In combining with self-adaptive schemes for mutation and crossover constants, this adaptive population reduction method can help shed light on the future direction of a completely parameter tune-free self-adaptive DE algorithm.

An adaptive inverse kinematics algorithm for robot manipulators

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.; Seraji, H.

1990-01-01

An adaptive algorithm for solving the inverse kinematics problem for robot manipulators is presented. The algorithm is derived using model reference adaptive control (MRAC) theory and is computationally efficient for online applications. The scheme requires no a priori knowledge of the kinematics of the robot if Cartesian end-effector sensing is available, and it requires knowledge of only the forward kinematics if joint position sensing is used. Computer simulation results are given for the redundant seven-DOF robotics research arm, demonstrating that the proposed algorithm yields accurate joint angle trajectories for a given end-effector position/orientation trajectory.

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

2002-01-01

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Adaptive Interventions in Drug Court: A Pilot Experiment

PubMed Central

Marlowe, Douglas B.; Festinger, David S.; Arabia, Patricia L.; Dugosh, Karen L.; Benasutti, Kathleen M.; Croft, Jason R.; McKay, James R.

2009-01-01

This pilot study (N = 30) experimentally examined the effects of an adaptive intervention in an adult misdemeanor drug court. The adaptive algorithm adjusted the frequency of judicial status hearings and clinical case-management sessions according to pre-specified criteria in response to participants' ongoing performance in the program. Results revealed the adaptive algorithm was acceptable to both clients and staff, feasible to implement with greater than 85% fidelity, and showed promise for eliciting clinically meaningful improvements in drug abstinence and graduation rates. Estimated effect sizes ranged from 0.40 to 0.60 across various dependent measures. Compared to drug court as-usual, participants in the adaptive condition were more likely to receive responses from the drug court team for inadequate performance in the program and received those responses after a substantially shorter period of time. This suggests the adaptive algorithm may have more readily focused the drug court team's attention on poorly-performing individuals, thus allowing the team to “nip problems in the bud” before they developed too fully. These preliminary data justify additional research evaluating the effects of the adaptive algorithm in a fully powered experimental trial. PMID:19724664

Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

NASA Technical Reports Server (NTRS)

Hunter, H. E.; Amato, R. A.

1972-01-01

The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Crawford, John P.; Drinkwater, Mark R.; Emery, William J.; Eppler, Duane T.; Farmer, L. Dennis; Fowler, Charles W.; Goodberlet, Mark; Jentz, Robert R.; Milman, Andrew

1992-01-01

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided.

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

NASA Astrophysics Data System (ADS)

Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

2017-10-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375 m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16+ year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms. These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

PubMed Central

Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

2016-01-01

Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938

A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

PubMed Central

Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207

A hybrid adaptive routing algorithm for event-driven wireless sensor networks.

PubMed

Figueiredo, Carlos M S; Nakamura, Eduardo F; Loureiro, Antonio A F

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption.

Parallel Algorithm Solves Coupled Differential Equations

NASA Technical Reports Server (NTRS)

Hayashi, A.

1987-01-01

Numerical methods adapted to concurrent processing. Algorithm solves set of coupled partial differential equations by numerical integration. Adapted to run on hypercube computer, algorithm separates problem into smaller problems solved concurrently. Increase in computing speed with concurrent processing over that achievable with conventional sequential processing appreciable, especially for large problems.

SIMULATION OF DISPERSION OF A POWER PLANT PLUME USING AN ADAPTIVE GRID ALGORITHM. (R827028)

EPA Science Inventory

A new dynamic adaptive grid algorithm has been developed for use in air quality modeling. This algorithm uses a higher order numerical scheme––the piecewise parabolic method (PPM)––for computing advective solution fields; a weight function capable o...

The NOAA-NASA CZCS Reanalysis Effort

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Conkright, Margarita E.; OReilly, John E.; Patt, Frederick S.; Wang, Meng-Hua; Yoder, James; Casey-McCabe, Nancy; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Satellite observations of global ocean chlorophyll span over two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the NOAA-NASA CZCS Reanalysis (NCR) Effort. NCR consisted of 1) algorithm improvement (AI), where CZCS processing algorithms were improved using modernized atmospheric correction and bio-optical algorithms, and 2) blending, where in situ data were incorporated into the CZCS AI to minimize residual errors. The results indicated major improvement over the previously available CZCS archive. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.

CNES-NASA Studies of the Mars Sample Return Orbiter Aerocapture Phase

NASA Technical Reports Server (NTRS)

Fraysse, H.; Powell, R.; Rousseau, S.; Striepe, S.

2000-01-01

A Mars Sample Return (MSR) mission has been proposed as a joint CNES (Centre National d'Etudes Spatiales) and NASA effort in the ongoing Mars Exploration Program. The MSR mission is designed to return the first samples of Martian soil to Earth. The primary elements of the mission are a lander, rover, ascent vehicle, orbiter, and an Earth entry vehicle. The Orbiter has been allocated only 2700 kg on the launch phase to perform its part of the mission. This mass restriction has led to the decision to use an aerocapture maneuver at Mars for the orbiter. Aerocapture replaces the initial propulsive capture maneuver with a single atmospheric pass. This atmospheric pass will result in the proper apoapsis, but a periapsis raise maneuver is required at the first apoapsis. The use of aerocapture reduces the total mass requirement by approx. 45% for the same payload. This mission will be the first to use the aerocapture technique. Because the spacecraft is flying through the atmosphere, guidance algorithms must be developed that will autonomously provide the proper commands to reach the desired orbit while not violating any of the design parameters (e.g. maximum deceleration, maximum heating rate, etc.). The guidance algorithm must be robust enough to account for uncertainties in delivery states, atmospheric conditions, mass properties, control system performance, and aerodynamics. To study this very critical phase of the mission, a joint CNES-NASA technical working group has been formed. This group is composed of atmospheric trajectory specialists from CNES, NASA Langley Research Center and NASA Johnson Space Center. This working group is tasked with developing and testing guidance algorithms, as well as cross-validating CNES and NASA flight simulators for the Mars atmospheric entry phase of this mission. The final result will be a recommendation to CNES on the algorithm to use, and an evaluation of the flight risks associated with the algorithm. This paper will describe the aerocapture phase of the MSR mission, the main principles of the guidance algorithms that are under development, the atmospheric entry simulators developed for the evaluations, the process for the evaluations, and preliminary results from the evaluations.

Hybrid adaptive ascent flight control for a flexible launch vehicle

NASA Astrophysics Data System (ADS)

Lefevre, Brian D.

For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the hybrid adaptive flight controller, development of a Newton's method based online parameter update that is modified to include a step size which regulates the rate of change in the parameter estimates, comparison of the modified Newton's method and recursive least squares online parameter update algorithms, modification of the neural network's input structure to accommodate for the nature of the nonlinearities present in a launch vehicle's ascent flight, examination of both tracking error based and modeling error based neural network weight update laws, and integration of feedback filters for the purpose of preventing harmful interaction between the flight control system and flexible structural modes. To validate the hybrid adaptive controller, a high-fidelity Ares I ascent flight simulator and a classical gain-scheduled proportional-integral-derivative (PID) ascent flight controller were obtained from the NASA Marshall Space Flight Center. The classical PID flight controller is used as a benchmark when analyzing the performance of the hybrid adaptive flight controller. Simulations are conducted which model both nominal and off-nominal flight conditions with structural flexibility of the vehicle either enabled or disabled. First, rigid body ascent simulations are performed with the hybrid adaptive controller under nominal flight conditions for the purpose of selecting the update laws which drive the indirect and direct adaptive components. With the neural network disabled, the results revealed that the recursive least squares online parameter update caused high frequency oscillations to appear in the engine gimbal commands. This is highly undesirable for long and slender launch vehicles, such as the Ares I, because such oscillation of the rocket nozzle could excite unstable structural flex modes. In contrast, the modified Newton's method online parameter update produced smooth control signals and was thus selected for use in the hybrid adaptive launch vehicle flight controller. In the simulations where the online parameter identification algorithm was disabled, the tracking error based neural network weight update law forced the network's output to diverge despite repeated reductions of the adaptive learning rate. As a result, the modeling error based neural network weight update law (which generated bounded signals) is utilized by the hybrid adaptive controller in all subsequent simulations. Comparing the PID and hybrid adaptive flight controllers under nominal flight conditions in rigid body ascent simulations showed that their tracking error magnitudes are similar for a period of time during the middle of the ascent phase. Though the PID controller performs better for a short interval around the 20 second mark, the hybrid adaptive controller performs far better from roughly 70 to 120 seconds. Elevating the aerodynamic loads by increasing the force and moment coefficients produced results very similar to the nominal case. However, applying a 5% or 10% thrust reduction to the first stage rocket motor causes the tracking error magnitude observed by the PID controller to be significantly elevated and diverge rapidly as the simulation concludes. In contrast, the hybrid adaptive controller steadily maintains smaller errors (often less than 50% of the corresponding PID value). Under the same sets of flight conditions with flexibility enabled, the results exhibit similar trends with the hybrid adaptive controller performing even better in each case. Again, the reduction of the first stage rocket motor's thrust clearly illustrated the superior robustness of the hybrid adaptive flight controller.

Quick fuzzy backpropagation algorithm.

PubMed

Nikov, A; Stoeva, S

2001-03-01

A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.

An Adaptive Tradeoff Algorithm for Multi-issue SLA Negotiation

NASA Astrophysics Data System (ADS)

Son, Seokho; Sim, Kwang Mong

Since participants in a Cloud may be independent bodies, mechanisms are necessary for resolving different preferences in leasing Cloud services. Whereas there are currently mechanisms that support service-level agreement negotiation, there is little or no negotiation support for concurrent price and timeslot for Cloud service reservations. For the concurrent price and timeslot negotiation, a tradeoff algorithm to generate and evaluate a proposal which consists of price and timeslot proposal is necessary. The contribution of this work is thus to design an adaptive tradeoff algorithm for multi-issue negotiation mechanism. The tradeoff algorithm referred to as "adaptive burst mode" is especially designed to increase negotiation speed and total utility and to reduce computational load by adaptively generating concurrent set of proposals. The empirical results obtained from simulations carried out using a testbed suggest that due to the concurrent price and timeslot negotiation mechanism with adaptive tradeoff algorithm: 1) both agents achieve the best performance in terms of negotiation speed and utility; 2) the number of evaluations of each proposal is comparatively lower than previous scheme (burst-N).

Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.

PubMed

Mei, Gang; Xu, Nengxiong; Xu, Liangliang

2016-01-01

This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm.

An overview of controls research on the NASA Langley Research Center grid

NASA Technical Reports Server (NTRS)

Montgomery, Raymond C.

1987-01-01

The NASA Langley Research Center has assembled a flexible grid on which control systems research can be accomplished on a two-dimensional structure that has many physically distributed sensors and actuators. The grid is a rectangular planar structure that is suspended by two cables attached to one edge so that out of plane vibrations are normal to gravity. There are six torque wheel actuators mounted to it so that torque is produced in the grid plane. Also, there are six rate gyros mounted to sense angular motion in the grid plane and eight accelerometers that measure linear acceleration normal to the grid plane. All components can be relocated to meet specific control system test requirements. Digital, analog, and hybrid control systems capability is provided in the apparatus. To date, research on this grid has been conducted in the areas of system and parameter identification, model estimation, distributed modal control, hierarchical adaptive control, and advanced redundancy management algorithms. The presentation overviews each technique and presents the most significant results generated for each area.

FPGA Control System for the Automated Test of Microshutters

NASA Technical Reports Server (NTRS)

Lyness, Eric; Rapchun, David A.; Moseley, S. Harvey

2008-01-01

The James Webb Space Telescope, scheduled to replace the Hubble in 2013, must simultaneously observe hundreds of faint galaxies. This requirement has led to the development of a programmable transmission mask which can be adapted to admit light with arbitrary pattern of galaxies into its spectrograph. This programmable mask will contain a large array of micro-electromechanical (MEMs) devices called MicroShutters. These microscopic shutters physically open and close like the shutter on a camera, except each shutter is microscopic in size and an array 365 by 171 is used to select the objects under spectroscopic observation at a given time, and to block the unwanted background light from other areas. NASA developed and is currently refining the exceptionally difficult process of manufacturing these shutters. This paper describes how the authors used LabVIEW FPGA and a reconfigurable I/O board to control the shutters in a test chamber and how the flexibility of the system allows us to continue to modify the control algorithms as NASA optimizes the performance of the MicroShutter arrays.

FPGA Control System for the Automated Test of MicroShutters

NASA Technical Reports Server (NTRS)

Lyness, Eric; Rapchun, David A.; Moseley, S. Harvey

2008-01-01

The James Webb Space Telescope, scheduled to replace the Hubble in 2013, must simultaneously observe hundreds of faint galaxies. This requirement has led to the development of a programmable transmission mask which can be adapted to admit light from an arbitrary pattern of galaxies into its spectrograph. This programmable mask will contain a large array of micro-electromechanical (MEMs) devices called MicroShutters. These microscopic shutters physically open and close like the shutter on a camera, except each shutter is microscopic in size and an array 365 by 171 is used to select the objects under spectroscopic observation at a given time, and to block the unwanted background light from other areas. NASA developed and is currently refining the exceptionally difficult process of manufacturing these shutters. This paper describes how the authors used LabVIEW FPGA and a reconfigurable I/O board to control the shutters in a test chamber and how the flexibility of the system allows us to continue to modify the control algorithms as NASA optimizes the performance of the MicroShutter arrays.

Proceedings of the Sixth NASA Langley Formal Methods (LFM) Workshop

NASA Technical Reports Server (NTRS)

Rozier, Kristin Yvonne (Editor)

2008-01-01

Today's verification techniques are hard-pressed to scale with the ever-increasing complexity of safety critical systems. Within the field of aeronautics alone, we find the need for verification of algorithms for separation assurance, air traffic control, auto-pilot, Unmanned Aerial Vehicles (UAVs), adaptive avionics, automated decision authority, and much more. Recent advances in formal methods have made verifying more of these problems realistic. Thus we need to continually re-assess what we can solve now and identify the next barriers to overcome. Only through an exchange of ideas between theoreticians and practitioners from academia to industry can we extend formal methods for the verification of ever more challenging problem domains. This volume contains the extended abstracts of the talks presented at LFM 2008: The Sixth NASA Langley Formal Methods Workshop held on April 30 - May 2, 2008 in Newport News, Virginia, USA. The topics of interest that were listed in the call for abstracts were: advances in formal verification techniques; formal models of distributed computing; planning and scheduling; automated air traffic management; fault tolerance; hybrid systems/hybrid automata; embedded systems; safety critical applications; safety cases; accident/safety analysis.

Three-dimensional geoelectric modelling with optimal work/accuracy rate using an adaptive wavelet algorithm

NASA Astrophysics Data System (ADS)

Plattner, A.; Maurer, H. R.; Vorloeper, J.; Dahmen, W.

2010-08-01

Despite the ever-increasing power of modern computers, realistic modelling of complex 3-D earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modelling approaches includes either finite difference or non-adaptive finite element algorithms and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behaviour of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modelled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet-based approach that is applicable to a large range of problems, also including nonlinear problems. In comparison with earlier applications of adaptive solvers to geophysical problems we employ here a new adaptive scheme whose core ingredients arose from a rigorous analysis of the overall asymptotically optimal computational complexity, including in particular, an optimal work/accuracy rate. Our adaptive wavelet algorithm offers several attractive features: (i) for a given subsurface model, it allows the forward modelling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient and (iii) the modelling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving 3-D geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best-fitting subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectric modelling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with high spatial variability of electrical conductivities. The linear dependence of the modelling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementation.

Multi-limit unsymmetrical MLIBD image restoration algorithm

NASA Astrophysics Data System (ADS)

Yang, Yang; Cheng, Yiping; Chen, Zai-wang; Bo, Chen

2012-11-01

A novel multi-limit unsymmetrical iterative blind deconvolution(MLIBD) algorithm was presented to enhance the performance of adaptive optics image restoration.The algorithm enhances the reliability of iterative blind deconvolution by introducing the bandwidth limit into the frequency domain of point spread(PSF),and adopts the PSF dynamic support region estimation to improve the convergence speed.The unsymmetrical factor is automatically computed to advance its adaptivity.Image deconvolution comparing experiments between Richardson-Lucy IBD and MLIBD were done,and the result indicates that the iteration number is reduced by 22.4% and the peak signal-to-noise ratio is improved by 10.18dB with MLIBD method. The performance of MLIBD algorithm is outstanding in the images restoration the FK5-857 adaptive optics and the double-star adaptive optics.

Hardware Acceleration of Adaptive Neural Algorithms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

James, Conrad D.

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - worldmore » conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.« less

A chaos wolf optimization algorithm with self-adaptive variable step-size

NASA Astrophysics Data System (ADS)

Zhu, Yong; Jiang, Wanlu; Kong, Xiangdong; Quan, Lingxiao; Zhang, Yongshun

2017-10-01

To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA) with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as "winner-take-all" and the update mechanism as "survival of the fittest" were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.

Exploiting Redundancy and Application Scalability for Cost-Effective, Time-Constrained Execution of HPC Applications on Amazon EC2

DOE PAGES

Marathe, Aniruddha P.; Harris, Rachel A.; Lowenthal, David K.; ...

2015-12-17

The use of clouds to execute high-performance computing (HPC) applications has greatly increased recently. Clouds provide several potential advantages over traditional supercomputers and in-house clusters. The most popular cloud is currently Amazon EC2, which provides fixed-cost and variable-cost, auction-based options. The auction market trades lower cost for potential interruptions that necessitate checkpointing; if the market price exceeds the bid price, a node is taken away from the user without warning. We explore techniques to maximize performance per dollar given a time constraint within which an application must complete. Specifically, we design and implement multiple techniques to reduce expected cost bymore » exploiting redundancy in the EC2 auction market. We then design an adaptive algorithm that selects a scheduling algorithm and determines the bid price. We show that our adaptive algorithm executes programs up to seven times cheaper than using the on-demand market and up to 44 percent cheaper than the best non-redundant, auction-market algorithm. We extend our adaptive algorithm to incorporate application scalability characteristics for further cost savings. In conclusion, we show that the adaptive algorithm informed with scalability characteristics of applications achieves up to 56 percent cost savings compared to the expected cost for the base adaptive algorithm run at a fixed, user-defined scale.« less

SLS Test Hardware Taken to Redstone Arsenal Airfield for Guppy Loading

NASA Image and Video Library

2017-07-10

A structural test article of the Orion Stage Adapter for NASA’s Space Launch System, built at NASA's Marshall Space Flight Center, is transported and prepared to be loaded onto NASA's Super Guppy aircraft. With integrated structural testing complete at Marshall, the stage adapter will soon be transported to Lockheed Martin in Denver for further testing with NASA's Orion spacecraft. The Guppy -- a plane large enough to carry cargo weighing more than 26 tons -- arrived at the U.S. Army's Redstone Arsenal Airfield July 10 to transport the stage adapter. On SLS's first integrated flight with Orion, the OSA will connect Orion to the Interim Cryogenic Propulsion Stage.

Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels

NASA Astrophysics Data System (ADS)

Stroeve, Julienne C.; Jenouvrier, Stephanie; Campbell, G. Garrett; Barbraud, Christophe; Delord, Karine

2016-08-01

Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.

NASA Hardware Heads to Kennedy For Flight Preparations

NASA Image and Video Library

2018-01-24

The Orion stage adapter will be part of the first integrated flight of NASA's heavy-lift rocket, the Space Launch System, and the Orion spacecraft. The adapter, approximately 5 feet tall and 18 feet in diameter, was designed and built at NASA's Marshall Space Flight Center in Huntsville, Alabama, with advanced friction stir welding technology. It will connect the SLS interim cryogenic propulsion stage to Orion on the first flight that will help engineers check out and verify the agency's new deep-space exploration systems. Inside the adapter, engineers installed special brackets and cabling for the 13 CubeSats that will fly as secondary payloads. The Cubesats are boot-box-sized science and technology investigations that will help pave the way for future human exploration in deep space. The Orion stage adapter flight article recently finished major testing of the avionics system that will deploy the CubeSats. Technicians at NASA's Kennedy Space Center, Florida, will install the secondary payloads and engineers will examine the hardware before it is stacked on the interim cryogenic propulsion stage in the Vehicle Assembly Building prior to launch. For more information about SLS hardware, visit nasa.gov/sls.

Toward Developing an Unbiased Scoring Algorithm for "NASA" and Similar Ranking Tasks.

ERIC Educational Resources Information Center

Lane, Irving M.; And Others

1981-01-01

Presents both logical and empirical evidence to illustrate that the conventional scoring algorithm for ranking tasks significantly underestimates the initial level of group ability and that Slevin's alternative scoring algorithm significantly overestimates the initial level of ability. Presents a modification of Slevin's algorithm which authors…

Runway Safety Monitor Algorithm for Single and Crossing Runway Incursion Detection and Alerting

NASA Technical Reports Server (NTRS)

Green, David F., Jr.

2006-01-01

The Runway Safety Monitor (RSM) is an aircraft based algorithm for runway incursion detection and alerting that was developed in support of NASA's Runway Incursion Prevention System (RIPS) research conducted under the NASA Aviation Safety and Security Program's Synthetic Vision System project. The RSM algorithm provides warnings of runway incursions in sufficient time for pilots to take evasive action and avoid accidents during landings, takeoffs or when taxiing on the runway. The report documents the RSM software and describes in detail how RSM performs runway incursion detection and alerting functions for NASA RIPS. The report also describes the RIPS flight tests conducted at the Reno/Tahoe International Airport (RNO) and the Wallops Flight Facility (WAL) during July and August of 2004, and the RSM performance results and lessons learned from those flight tests.

A homotopy method based on WENO schemes for solving steady state problems of hyperbolic conservation laws

DTIC Science & Technology

2012-09-03

prac- tice to solve these initial value problems. Additionally, the predictor / corrector methods are combined with adaptive stepsize and adaptive ...for implementing a numerical path tracking algorithm is to decide which predictor / corrector method to employ, how large to take the step ∆t, and what...the endgame algorithm . Output: A steady state solution Set ǫ = 1 while ǫ >= ǫend do set the stepsize ∆ǫ by using adaptive stepsize control algorithm

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows

PubMed Central

Jawarneh, Sana; Abdullah, Salwani

2015-01-01

This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon’s 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results. PMID:26132158

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Accelerated Dimension-Independent Adaptive Metropolis

DOE PAGES

Chen, Yuxin; Keyes, David E.; Law, Kody J.; ...

2016-10-27

This work describes improvements from algorithmic and architectural means to black-box Bayesian inference over high-dimensional parameter spaces. The well-known adaptive Metropolis (AM) algorithm [33] is extended herein to scale asymptotically uniformly with respect to the underlying parameter dimension for Gaussian targets, by respecting the variance of the target. The resulting algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional (with dimension d 1000) targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justimore » ed a posteriori). Asymptotically in dimension, this GPU implementation exhibits a factor of four improvement versus a competitive CPU-based Intel MKL parallel version alone. Strong scaling to concurrent chains is exhibited, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. The algorithm performance is illustrated on several Gaussian and non-Gaussian target examples, in which the dimension may be in excess of one thousand.« less

Accelerated Dimension-Independent Adaptive Metropolis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuxin; Keyes, David E.; Law, Kody J.

This work describes improvements from algorithmic and architectural means to black-box Bayesian inference over high-dimensional parameter spaces. The well-known adaptive Metropolis (AM) algorithm [33] is extended herein to scale asymptotically uniformly with respect to the underlying parameter dimension for Gaussian targets, by respecting the variance of the target. The resulting algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional (with dimension d 1000) targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justimore » ed a posteriori). Asymptotically in dimension, this GPU implementation exhibits a factor of four improvement versus a competitive CPU-based Intel MKL parallel version alone. Strong scaling to concurrent chains is exhibited, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. The algorithm performance is illustrated on several Gaussian and non-Gaussian target examples, in which the dimension may be in excess of one thousand.« less

Fast Adapting Ensemble: A New Algorithm for Mining Data Streams with Concept Drift

PubMed Central

Ortíz Díaz, Agustín; Ramos-Jiménez, Gonzalo; Frías Blanco, Isvani; Caballero Mota, Yailé; Morales-Bueno, Rafael

2015-01-01

The treatment of large data streams in the presence of concept drifts is one of the main challenges in the field of data mining, particularly when the algorithms have to deal with concepts that disappear and then reappear. This paper presents a new algorithm, called Fast Adapting Ensemble (FAE), which adapts very quickly to both abrupt and gradual concept drifts, and has been specifically designed to deal with recurring concepts. FAE processes the learning examples in blocks of the same size, but it does not have to wait for the batch to be complete in order to adapt its base classification mechanism. FAE incorporates a drift detector to improve the handling of abrupt concept drifts and stores a set of inactive classifiers that represent old concepts, which are activated very quickly when these concepts reappear. We compare our new algorithm with various well-known learning algorithms, taking into account, common benchmark datasets. The experiments show promising results from the proposed algorithm (regarding accuracy and runtime), handling different types of concept drifts. PMID:25879051

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

NASA Astrophysics Data System (ADS)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

Algorithms for the Computation of Debris Risks

NASA Technical Reports Server (NTRS)

Matney, Mark

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of non-spherical satellites. A number of tools have been developed in NASA's Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA's Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper will present an introduction to these algorithms and the assumptions upon which they are based.

Evolvable Hardware for Space Applications

NASA Technical Reports Server (NTRS)

Lohn, Jason; Globus, Al; Hornby, Gregory; Larchev, Gregory; Kraus, William

2004-01-01

This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.

RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems

NASA Technical Reports Server (NTRS)

Pecheur, Charles; Visser, Willem; Simmons, Reid

2001-01-01

The long-term future of space exploration at NASA is dependent on the full exploitation of autonomous and adaptive systems: careful monitoring of missions from earth, as is the norm now, will be infeasible due to the sheer number of proposed missions and the communication lag for deep-space missions. Mission managers are however worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries and hence we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation (V&V) of software systems. The dual purpose of the meeting was to: (1) make NASA engineers aware of the V&V techniques they could be using; and (2) make the V&V community aware of the complexity of the systems NASA is developing.

Implementation of LSCMA adaptive array terminal for mobile satellite communications

NASA Astrophysics Data System (ADS)

Zhou, Shun; Wang, Huali; Xu, Zhijun

2007-11-01

This paper considers the application of adaptive array antenna based on the least squares constant modulus algorithm (LSCMA) for interference rejection in mobile SATCOM terminals. A two-element adaptive array scheme is implemented with a combination of ADI TS201S DSP chips and Altera Stratix II FPGA device, which makes a cooperating computation for adaptive beamforming. Its interference suppressing performance is verified via Matlab simulations. Digital hardware system is implemented to execute the operations of LSCMA beamforming algorithm that is represented by an algorithm flowchart. The result of simulations and test indicate that this scheme can improve the anti-jamming performance of terminals.

An adaptive interpolation scheme for molecular potential energy surfaces

NASA Astrophysics Data System (ADS)

Kowalewski, Markus; Larsson, Elisabeth; Heryudono, Alfa

2016-08-01

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task—especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior are evaluated for a model function in 2, 3, and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within a given accuracy compared to the non-adaptive version.

Robust local search for spacecraft operations using adaptive noise

NASA Technical Reports Server (NTRS)

Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

2004-01-01

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

An Experimental Evaluation of Generalized Predictive Control for Tiltrotor Aeroelastic Stability Augmentation in Airplane Mode of Flight

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.; Piatak, David J.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.

2001-01-01

The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of Generalized Predictive Control (GPC) for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in the airplane mode of flight are presented. GPC is an adaptive time-domain predictive control method that uses a linear difference equation to describe the input-output relationship of the system and to design the controller. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 that was modified to incorporate a GPC-based multi-input multi-output control algorithm to individually control each of the three swashplate actuators. Wing responses were used for feedback. The GPC-based control system was highly effective in increasing the stability of the critical wing mode for all of the conditions tested, without measurable degradation of the damping in the other modes. The algorithm was also robust with respect to its performance in adjusting to rapid changes in both the rotor speed and the tunnel airspeed.

Tiltrotor Vibration Reduction Through Higher Harmonic Control

NASA Technical Reports Server (NTRS)

Nixon, Mark W.; Kvaternik, Raymond G.; Settle, T. Ben

1997-01-01

The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of higher harmonic control (HHC) for reducing vibrations in tiltrotor aircraft operating in the airplane mode of flight, and to evaluate the effectiveness of a Bell-developed HHC algorithm called MAVSS (Multipoint Adaptive Vibration Suppression System) are presented. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 which was modified to incorporate an HHC system employing both the rotor swashplate and the wing flaperon. The effectiveness of the swashplate and the flaperon acting either singly or in combination in reducing IP and 3P wing vibrations over a wide range of tunnel airspeeds and rotor rotational speeds was demonstrated. The MAVSS algorithm was found to be robust to variations in tunnel airspeed and rotor speed, requiring only occasional on-line recalculations of the system transfer matrix. HHC had only a small (usually beneficial) effect on blade loads but increased pitch link loads by 25%. No degradation in aeroelastic stability was noted for any of the conditions tested.

An improved conscan algorithm based on a Kalman filter

NASA Technical Reports Server (NTRS)

Eldred, D. B.

1994-01-01

Conscan is commonly used by DSN antennas to allow adaptive tracking of a target whose position is not precisely known. This article describes an algorithm that is based on a Kalman filter and is proposed to replace the existing fast Fourier transform based (FFT-based) algorithm for conscan. Advantages of this algorithm include better pointing accuracy, continuous update information, and accommodation of missing data. Additionally, a strategy for adaptive selection of the conscan radius is proposed. The performance of the algorithm is illustrated through computer simulations and compared to the FFT algorithm. The results show that the Kalman filter algorithm is consistently superior.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert M.

2013-01-01

A new regression model search algorithm was developed that may be applied to both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The algorithm is a simplified version of a more complex algorithm that was originally developed for the NASA Ames Balance Calibration Laboratory. The new algorithm performs regression model term reduction to prevent overfitting of data. It has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a regression model search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression model. Therefore, the simplified algorithm is not intended to replace the original algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new search algorithm.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2013-01-01

A new regression model search algorithm was developed in 2011 that may be used to analyze both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The new algorithm is a simplified version of a more complex search algorithm that was originally developed at the NASA Ames Balance Calibration Laboratory. The new algorithm has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression models. Therefore, the simplified search algorithm is not intended to replace the original search algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm either fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new regression model search algorithm.

Climate risks workshop

NASA Image and Video Library

2012-10-16

Participants in an Oct. 16-18 workshop at John C. Stennis Space Center focused on identifying current and future climate risks and developing strategies to address them. NASA Headquarters sponsored the Resilience and Adaptation to Climate Risks Workshop to understand climate change risks and adaptation strategies. The workshop was part of an effort that joins the science and operations arms of the agency in a coordinated response to climate change. NASA Headquarters is holding workshops on the subject at all NASA centers.

Adaptive Wavelet Modeling of Geophysical Data

NASA Astrophysics Data System (ADS)

Plattner, A.; Maurer, H.; Dahmen, W.; Vorloeper, J.

2009-12-01

Despite the ever-increasing power of modern computers, realistic modeling of complex three-dimensional Earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modeling approaches includes either finite difference or non-adaptive finite element algorithms, and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behavior of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modeled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet based approach that is applicable to a large scope of problems, also including nonlinear problems. To the best of our knowledge such algorithms have not yet been applied in geophysics. Adaptive wavelet algorithms offer several attractive features: (i) for a given subsurface model, they allow the forward modeling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient, and (iii) the modeling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving three-dimensional geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best fit subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectrical modeling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with spatially highly variable electrical conductivities. The linear dependency of the modeling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementation.

Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

2013-01-01

This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

Application of adaptive filters in denoising magnetocardiogram signals

NASA Astrophysics Data System (ADS)

Khan, Pathan Fayaz; Patel, Rajesh; Sengottuvel, S.; Saipriya, S.; Swain, Pragyna Parimita; Gireesan, K.

2017-05-01

Magnetocardiography (MCG) is the measurement of weak magnetic fields from the heart using Superconducting QUantum Interference Devices (SQUID). Though the measurements are performed inside magnetically shielded rooms (MSR) to reduce external electromagnetic disturbances, interferences which are caused by sources inside the shielded room could not be attenuated. The work presented here reports the application of adaptive filters to denoise MCG signals. Two adaptive noise cancellation approaches namely least mean squared (LMS) algorithm and recursive least squared (RLS) algorithm are applied to denoise MCG signals and the results are compared. It is found that both the algorithms effectively remove noisy wiggles from MCG traces; significantly improving the quality of the cardiac features in MCG traces. The calculated signal-to-noise ratio (SNR) for the denoised MCG traces is found to be slightly higher in the LMS algorithm as compared to the RLS algorithm. The results encourage the use of adaptive techniques to suppress noise due to power line frequency and its harmonics which occur frequently in biomedical measurements.

NOAA-NASA Coastal Zone Color Scanner reanalysis effort.

PubMed

Gregg, Watson W; Conkright, Margarita E; O'Reilly, John E; Patt, Frederick S; Wang, Menghua H; Yoder, James A; Casey, Nancy W

2002-03-20

Satellite observations of global ocean chlorophyll span more than two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration (NOAA-NASA) CZCS reanalysis (NCR) effort. NCR consisted of (1) algorithm improvement (AI), where CZCS processing algorithms were improved with modernized atmospheric correction and bio-optical algorithms and (2) blending where in situ data were incorporated into the CZCS AI to minimize residual errors. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.

Lessons Learned from Inlet Integration Analysis of NASA's Low Boom Flight Demonstrator

NASA Technical Reports Server (NTRS)

Friedlander, David; Heath, Christopher; Castner, Ray

2017-01-01

In 2016, NASA's Aeronautics Research Mission Directorate announced the New Aviation Horizons Initiative with a goal of designing/building several X-Planes, including a Low Boom Flight Demonstrator (LBFD). That same year, NASA awarded a contract to Lockheed Martin (LM) to advance the LBFD concept through preliminary design. Several configurations of the LBFD aircraft were analyzed by both LM engineers and NASA researchers. This presentation focuses on some of the CFD simulations that were run by NASA Glenn researchers. NASA's FUN3D V13.1 code was used for all adjoint-based grid refinement studies and Spalart-Allmaras turbulence model was used during adaptation. It was found that adjoint-based grid adaptation did not accurately capture inlet performance for high speed top-aft-mounted propulsion.

Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed

NASA Technical Reports Server (NTRS)

Tian, Ye; Song, Qi; Cattafesta, Louis

2005-01-01

This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.

Adaptive Control Strategies for Flexible Robotic Arm

NASA Technical Reports Server (NTRS)

Bialasiewicz, Jan T.

1996-01-01

The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Bayesian Analysis for Exponential Random Graph Models Using the Adaptive Exchange Sampler.

PubMed

Jin, Ick Hoon; Yuan, Ying; Liang, Faming

2013-10-01

Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the intractable normalizing constant and model degeneracy. In this paper, we consider a fully Bayesian analysis for exponential random graph models using the adaptive exchange sampler, which solves the intractable normalizing constant and model degeneracy issues encountered in Markov chain Monte Carlo (MCMC) simulations. The adaptive exchange sampler can be viewed as a MCMC extension of the exchange algorithm, and it generates auxiliary networks via an importance sampling procedure from an auxiliary Markov chain running in parallel. The convergence of this algorithm is established under mild conditions. The adaptive exchange sampler is illustrated using a few social networks, including the Florentine business network, molecule synthetic network, and dolphins network. The results indicate that the adaptive exchange algorithm can produce more accurate estimates than approximate exchange algorithms, while maintaining the same computational efficiency.

L(sub 1) Adaptive Control Design for NASA AirSTAR Flight Test Vehicle

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Cao, Chengyu; Hovakimyan, Naira; Zou, Xiaotian

2009-01-01

In this paper we present a new L(sub 1) adaptive control architecture that directly compensates for matched as well as unmatched system uncertainty. To evaluate the L(sub 1) adaptive controller, we take advantage of the flexible research environment with rapid prototyping and testing of control laws in the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. We apply the L(sub 1) adaptive control laws to the subscale turbine powered Generic Transport Model. The presented results are from a full nonlinear simulation of the Generic Transport Model and some preliminary pilot evaluations of the L(sub 1) adaptive control law.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tumuluru, Jaya Shankar; McCulloch, Richard Chet James

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the mostmore » improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.« less

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking †

PubMed Central

Kiku, Daisuke; Okutomi, Masatoshi

2017-01-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. PMID:29194407

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

PubMed

Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

2017-12-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

Improved Algorithm For Finite-Field Normal-Basis Multipliers

NASA Technical Reports Server (NTRS)

Wang, C. C.

1989-01-01

Improved algorithm reduces complexity of calculations that must precede design of Massey-Omura finite-field normal-basis multipliers, used in error-correcting-code equipment and cryptographic devices. Algorithm represents an extension of development reported in "Algorithm To Design Finite-Field Normal-Basis Multipliers" (NPO-17109), NASA Tech Briefs, Vol. 12, No. 5, page 82.

1301253

NASA Image and Video Library

2013-12-12

JASON ELDRIDGE, AN ERC INCORPORATED EMPLOYEE SUPPORTING THE MATERIALS & PROCESSES LABORATORY AT NASA'S MARSHALL SPACE FLIGHT CENTER, SIGNS HIS NAME ON THE INTERIOR OF THE ADAPTER THAT WILL CONNECT THE ORION SPACECRAFT TO A UNITED LAUNCH ALLIANCE DELTA IV ROCKET FOR EXPLORATION FLIGHT TEST (EFT)-1. MARSHALL CENTER TEAM MEMBERS WHO WERE INVOLVED IN THE DESIGN, CONSTRUCTION AND TESTING OF THE ADAPTER HAD THE OPPORTUNITY TO AUTOGRAPH IT BEFORE THE HARDWARE IS SHIPPED TO NASA'S KENNEDY SPACE CENTER IN FEBRUARY. ELDRIDGE WAS ON A TEAM THAT PERFORMED ULTRASONIC INSPECTIONS ON THE ADAPTER'S WELDS -- ENSURING THEY ARE STRUCTURALLY SOUND. EFT-1, SCHEDULED FOR 2014, WILL PROVIDE EARLY EXPERIENCE FOR NASA SPACE LAUNCH SYSTEM (SLS) HARDWARE AHEAD OF THE ROCKET'S FIRST FLIGHT IN 2017.

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

NASA Technical Reports Server (NTRS)

Al-Jiboory, Ali Khudhair; Zhu, Guoming; Swei, Sean Shan-Min; Su, Weihua; Nguyen, Nhan T.

2017-01-01

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

An adaptive SVSF-SLAM algorithm to improve the success and solving the UGVs cooperation problem

NASA Astrophysics Data System (ADS)

Demim, Fethi; Nemra, Abdelkrim; Louadj, Kahina; Hamerlain, Mustapha; Bazoula, Abdelouahab

2018-05-01

This paper aims to present a Decentralised Cooperative Simultaneous Localization and Mapping (DCSLAM) solution based on 2D laser data using an Adaptive Covariance Intersection (ACI). The ACI-DCSLAM algorithm will be validated on a swarm of Unmanned Ground Vehicles (UGVs) receiving features to estimate the position and covariance of shared features before adding them to the global map. With the proposed solution, a group of (UGVs) will be able to construct a large reliable map and localise themselves within this map without any user intervention. The most popular solutions to this problem are the EKF-SLAM, Nonlinear H-infinity ? SLAM and the FAST-SLAM. The former suffers from two important problems which are the poor consistency caused by the linearization problem and the calculation of Jacobian. The second solution is the ? which is a very promising filter because it doesn't make any assumption about noise characteristics, while the latter is not suitable for real time implementation. Therefore, a new alternative solution based on the smooth variable structure filter (SVSF) is adopted. Cooperative adaptive SVSF-SLAM algorithm is proposed in this paper to solve the UGVs SLAM problem. Our main contribution consists in adapting the SVSF filter to solve the Decentralised Cooperative SLAM problem for multiple UGVs. The algorithms developed in this paper were implemented using two mobile robots Pioneer ?, equiped with 2D laser telemetry sensors. Good results are obtained by the Cooperative adaptive SVSF-SLAM algorithm compared to the Cooperative EKF/?-SLAM algorithms, especially when the noise is colored or affected by a variable bias. Simulation results confirm and show the efficiency of the proposed algorithm which is more robust, stable and adapted to real time applications.

Concepts for on-board satellite image registration, volume 1

NASA Technical Reports Server (NTRS)

Ruedger, W. H.; Daluge, D. R.; Aanstoos, J. V.

1980-01-01

The NASA-NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. One very specific area of interest is the preprocessing required to register imaging sensor data which have been distorted by anomalies in subsatellite-point position and/or attitude control. The concepts and considerations involved in using state-of-the-art positioning systems such as the Global Positioning System (GPS) in concert with state-of-the-art attitude stabilization and/or determination systems to provide the required registration accuracy are discussed with emphasis on assessing the accuracy to which a given image picture element can be located and identified, determining those algorithms required to augment the registration procedure and evaluating the technology impact on performing these procedures on-board the satellite.

North American Fuzzy Logic Processing Society (NAFIPS 1992), volume 1

NASA Technical Reports Server (NTRS)

Villarreal, James A. (Compiler)

1992-01-01

This document contains papers presented at the NAFIPS '92 North American Fuzzy Information Processing Society Conference. More than 75 papers were presented at this Conference, which was sponsored by NAFIPS in cooperation with NASA, the Instituto Tecnologico de Morelia, the Indian Society for Fuzzy Mathematics and Information Processing (ISFUMIP), the Instituto Tecnologico de Estudios Superiores de Monterrey (ITESM), the International Fuzzy Systems Association (IFSA), the Japan Society for Fuzzy Theory and Systems, and the Microelectronics and Computer Technology Corporation (MCC). The fuzzy set theory has led to a large number of diverse applications. Recently, interesting applications have been developed which involve the integration of fuzzy systems with adaptive processes such as neural networks and genetic algorithms. NAFIPS '92 was directed toward the advancement, commercialization, and engineering development of these technologies.

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

NASA Technical Reports Server (NTRS)

Ruedger, W. H.; Aanstoos, J. V.; Snyder, W. E.

1982-01-01

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

North American Fuzzy Logic Processing Society (NAFIPS 1992), volume 2

NASA Technical Reports Server (NTRS)

Villarreal, James A. (Compiler)

1992-01-01

This document contains papers presented at the NAFIPS '92 North American Fuzzy Information Processing Society Conference. More than 75 papers were presented at this Conference, which was sponsored by NAFIPS in cooperation with NASA, the Instituto Tecnologico de Morelia, the Indian Society for Fuzzy Mathematics and Information Processing (ISFUMIP), the Instituto Tecnologico de Estudios Superiores de Monterrey (ITESM), the International Fuzzy Systems Association (IFSA), the Japan Society for Fuzzy Theory and Systems, and the Microelectronics and Computer Technology Corporation (MCC). The fuzzy set theory has led to a large number of diverse applications. Recently, interesting applications have been developed which involve the integration of fuzzy systems with adaptive processes such a neural networks and genetic algorithms. NAFIPS '92 was directed toward the advancement, commercialization, and engineering development of these technologies.

The Impact of Receiving the Same Items on Consecutive Computer Adaptive Test Administrations.

ERIC Educational Resources Information Center

O'Neill, Thomas; Lunz, Mary E.; Thiede, Keith

2000-01-01

Studied item exposure in a computerized adaptive test when the item selection algorithm presents examinees with questions they were asked in a previous test administration. Results with 178 repeat examinees on a medical technologists' test indicate that the combined use of an adaptive algorithm to select items and latent trait theory to estimate…

Slower speed and stronger coupling: adaptive mechanisms of chaos synchronization.

PubMed

Wang, Xiao Fan

2002-06-01

We show that two initially weakly coupled chaotic systems can achieve synchronization by adaptively reducing their speed and/or enhancing the coupling strength. Explicit adaptive algorithms for speed reduction and coupling enhancement are provided. We apply these algorithms to the synchronization of two coupled Lorenz systems. It is found that after a long-time adaptive process, the two coupled chaotic systems can achieve synchronization with almost the minimum required coupling-speed ratio.

Multiscale computations with a wavelet-adaptive algorithm

NASA Astrophysics Data System (ADS)

Rastigejev, Yevgenii Anatolyevich

A wavelet-based adaptive multiresolution algorithm for the numerical solution of multiscale problems governed by partial differential equations is introduced. The main features of the method include fast algorithms for the calculation of wavelet coefficients and approximation of derivatives on nonuniform stencils. The connection between the wavelet order and the size of the stencil is established. The algorithm is based on the mathematically well established wavelet theory. This allows us to provide error estimates of the solution which are used in conjunction with an appropriate threshold criteria to adapt the collocation grid. The efficient data structures for grid representation as well as related computational algorithms to support grid rearrangement procedure are developed. The algorithm is applied to the simulation of phenomena described by Navier-Stokes equations. First, we undertake the study of the ignition and subsequent viscous detonation of a H2 : O2 : Ar mixture in a one-dimensional shock tube. Subsequently, we apply the algorithm to solve the two- and three-dimensional benchmark problem of incompressible flow in a lid-driven cavity at large Reynolds numbers. For these cases we show that solutions of comparable accuracy as the benchmarks are obtained with more than an order of magnitude reduction in degrees of freedom. The simulations show the striking ability of the algorithm to adapt to a solution having different scales at different spatial locations so as to produce accurate results at a relatively low computational cost.

On adaptive learning rate that guarantees convergence in feedforward networks.

PubMed

Behera, Laxmidhar; Kumar, Swagat; Patnaik, Awhan

2006-09-01

This paper investigates new learning algorithms (LF I and LF II) based on Lyapunov function for the training of feedforward neural networks. It is observed that such algorithms have interesting parallel with the popular backpropagation (BP) algorithm where the fixed learning rate is replaced by an adaptive learning rate computed using convergence theorem based on Lyapunov stability theory. LF II, a modified version of LF I, has been introduced with an aim to avoid local minima. This modification also helps in improving the convergence speed in some cases. Conditions for achieving global minimum for these kind of algorithms have been studied in detail. The performances of the proposed algorithms are compared with BP algorithm and extended Kalman filtering (EKF) on three bench-mark function approximation problems: XOR, 3-bit parity, and 8-3 encoder. The comparisons are made in terms of number of learning iterations and computational time required for convergence. It is found that the proposed algorithms (LF I and II) are much faster in convergence than other two algorithms to attain same accuracy. Finally, the comparison is made on a complex two-dimensional (2-D) Gabor function and effect of adaptive learning rate for faster convergence is verified. In a nutshell, the investigations made in this paper help us better understand the learning procedure of feedforward neural networks in terms of adaptive learning rate, convergence speed, and local minima.

Integrated G and C Implementation within IDOS: A Simulink Based Reusable Launch Vehicle Simulation

NASA Technical Reports Server (NTRS)

Fisher, Joseph E.; Bevacqua, Tim; Lawrence, Douglas A.; Zhu, J. Jim; Mahoney, Michael

2003-01-01

The implementation of multiple Integrated Guidance and Control (IG&C) algorithms per flight phase within a vehicle simulation poses a daunting task to coordinate algorithm interactions with the other G&C components and with vehicle subsystems. Currently being developed by Universal Space Lines LLC (USL) under contract from NASA, the Integrated Development and Operations System (IDOS) contains a high fidelity Simulink vehicle simulation, which provides a means to test cutting edge G&C technologies. Combining the modularity of this vehicle simulation and Simulink s built-in primitive blocks provide a quick way to implement algorithms. To add discrete-event functionality to the unfinished IDOS simulation, Vehicle Event Manager (VEM) and Integrated Vehicle Health Monitoring (IVHM) subsystems were created to provide discrete-event and pseudo-health monitoring processing capabilities. Matlab's Stateflow is used to create the IVHM and Event Manager subsystems and to implement a supervisory logic controller referred to as the Auto-commander as part of the IG&C to coordinate the control system adaptation and reconfiguration and to select the control and guidance algorithms for a given flight phase. Manual creation of the Stateflow charts for all of these subsystems is a tedious and time-consuming process. The Stateflow Auto-builder was developed as a Matlab based software tool for the automatic generation of a Stateflow chart from information contained in a database. This paper describes the IG&C, VEM and IVHM implementations in IDOS. In addition, this paper describes the Stateflow Auto-builder.

An adaptive interpolation scheme for molecular potential energy surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kowalewski, Markus, E-mail: mkowalew@uci.edu; Larsson, Elisabeth; Heryudono, Alfa

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task—especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior are evaluated for a model function in 2, 3, and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within amore » given accuracy compared to the non-adaptive version.« less

Space communications scheduler: A rule-based approach to adaptive deadline scheduling

NASA Technical Reports Server (NTRS)

Straguzzi, Nicholas

1990-01-01

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

Auto-Generated Semantic Processing Services

NASA Technical Reports Server (NTRS)

Davis, Rodney; Hupf, Greg

2009-01-01

Auto-Generated Semantic Processing (AGSP) Services is a suite of software tools for automated generation of other computer programs, denoted cross-platform semantic adapters, that support interoperability of computer-based communication systems that utilize a variety of both new and legacy communication software running in a variety of operating- system/computer-hardware combinations. AGSP has numerous potential uses in military, space-exploration, and other government applications as well as in commercial telecommunications. The cross-platform semantic adapters take advantage of common features of computer- based communication systems to enforce semantics, messaging protocols, and standards of processing of streams of binary data to ensure integrity of data and consistency of meaning among interoperating systems. The auto-generation aspect of AGSP Services reduces development time and effort by emphasizing specification and minimizing implementation: In effect, the design, building, and debugging of software for effecting conversions among complex communication protocols, custom device mappings, and unique data-manipulation algorithms is replaced with metadata specifications that map to an abstract platform-independent communications model. AGSP Services is modular and has been shown to be easily integrable into new and legacy NASA flight and ground communication systems.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited

PubMed Central

Verstraete, Hans R. G. W.; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Jian, Yifan; Verhaegen, Michel; Sarunic, Marinko V.

2017-01-01

In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented. PMID:28736670

Wavefront sensorless adaptive optics OCT with the DONE algorithm for in vivo human retinal imaging [Invited].

PubMed

Verstraete, Hans R G W; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Jian, Yifan; Verhaegen, Michel; Sarunic, Marinko V

2017-04-01

In this report, which is an international collaboration of OCT, adaptive optics, and control research, we demonstrate the Data-based Online Nonlinear Extremum-seeker (DONE) algorithm to guide the image based optimization for wavefront sensorless adaptive optics (WFSL-AO) OCT for in vivo human retinal imaging. The ocular aberrations were corrected using a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators. The DONE algorithm succeeded in drastically improving image quality and the OCT signal intensity, up to a factor seven, while achieving a computational time of 1 ms per iteration, making it applicable for many high speed applications. We demonstrate the correction of five aberrations using 70 iterations of the DONE algorithm performed over 2.8 s of continuous volumetric OCT acquisition. Data acquired from an imaging phantom and in vivo from human research volunteers are presented.

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

NASA Technical Reports Server (NTRS)

Figueiredo, Marco A.; Gloster, Clay S.; Stephens, Mark; Graves, Corey A.; Nakkar, Mouna

1999-01-01

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

NASA Technical Reports Server (NTRS)

Jagge, Amy

2016-01-01

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Adaptive image coding based on cubic-spline interpolation

NASA Astrophysics Data System (ADS)

Jiang, Jian-Xing; Hong, Shao-Hua; Lin, Tsung-Ching; Wang, Lin; Truong, Trieu-Kien

2014-09-01

It has been investigated that at low bit rates, downsampling prior to coding and upsampling after decoding can achieve better compression performance than standard coding algorithms, e.g., JPEG and H. 264/AVC. However, at high bit rates, the sampling-based schemes generate more distortion. Additionally, the maximum bit rate for the sampling-based scheme to outperform the standard algorithm is image-dependent. In this paper, a practical adaptive image coding algorithm based on the cubic-spline interpolation (CSI) is proposed. This proposed algorithm adaptively selects the image coding method from CSI-based modified JPEG and standard JPEG under a given target bit rate utilizing the so called ρ-domain analysis. The experimental results indicate that compared with the standard JPEG, the proposed algorithm can show better performance at low bit rates and maintain the same performance at high bit rates.

NASA/GEWEX Surface Radiation Budget: Integrated Data Product With Reprocessed Radiance, Cloud, and Meteorology Inputs, and New Surface Albedo Treatment

NASA Technical Reports Server (NTRS)

Cox, Stephen J.; Stackhouse, Paul W., Jr.; Gupta, Shashi K.; Mikovitz, J. Colleen; Zhang, Taiping

2016-01-01

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current release 3.0 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number will allow SRB a higher resolution gridded product (e.g. 0.5 degree), as well as the production of pixel-level fluxes. In addition to the input data improvements, several important algorithm improvements have been made. Most notable has been the adaptation of Angular Distribution Models (ADMs) from CERES to improve the initial calculation of shortwave TOA fluxes, from which the surface flux calculations follow. Other key input improvements include a detailed aerosol history using the Max Planck Institut Aerosol Climatology (MAC), temperature and moisture profiles from HIRS, and new topography, surface type, and snow/ice. Here we present results for the improved GEWEX Shortwave and Longwave algorithm (GSW and GLW) with new ISCCP data, the various other improved input data sets and the incorporation of many additional internal SRB model improvements. As of the time of abstract submission, results from 2007 have been produced with ISCCP H availability the limiting factor. More SRB data will be produced as ISCCP reprocessing continues. The SRB data produced will be released as part of the Release 4.0 Integrated Product, recognizing the interdependence of the radiative fluxes with other GEWEX products providing estimates of the Earth's global water and energy cycle (I.e., ISCCP, SeaFlux, LandFlux, NVAP, etc.).

NASA/GEWEX Surface Radiation Budget: First Results From The Release 4 GEWEX Integrated Data Products

NASA Astrophysics Data System (ADS)

Stackhouse, Paul; Cox, Stephen; Gupta, Shashi; Mikovitz, J. Colleen; zhang, taiping

2016-04-01

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current release 3 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number should help improve the RMS of the existing products and allow for future higher resolution SRB gridded product (e.g. 0.5 degree). In addition to the input data improvements, several important algorithm improvements have been made. Most notable has been the adaptation of Angular Distribution Models (ADMs) from CERES to improve the initial calculation of shortwave TOA fluxes, from which the surface flux calculations follow. Other key input improvements include a detailed aerosol history using the Max Planck Institut Aerosol Climatology (MAC), temperature and moisture profiles from HIRS, and new topography, surface type, and snow/ice. Here we present results for the improved GEWEX Shortwave and Longwave algorithm (GSW and GLW) with new ISCCP data, the various other improved input data sets and the incorporation of many additional internal SRB model improvements. As of the time of abstract submission, results from 2007 have been produced with ISCCP H availability the limiting factor. More SRB data will be produced as ISCCP reprocessing continues. The SRB data produced will be released as part of the Release 4.0 Integrated Product, recognizing the interdependence of the radiative fluxes with other GEWEX products providing estimates of the Earth's global water and energy cycle (I.e., ISCCP, SeaFlux, LandFlux, NVAP, etc.).

Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum.

PubMed

Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Dean, Paul; Anderson, Sean R; Porrill, John

2015-01-01

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

NASA is with you when you fly on This Week @NASA - November 21, 2014NASA invited social media members Nov. 18 and 19 to the agency’s Armstrong Flight Research Center for a two-day event highlighting the ways NASA is with you when you fly. The NASA social gave participants an exclusive look at the latest tools and technologies being developed to improve the efficiency, safety and adaptability of air transportation. Also, Next ISS crew trains, 3D printer installed in space, Asteroid capture technology test, Journey to Mars media day and more!

NASA Image and Video Library

2014-11-21

NASA invited social media members Nov. 18 and 19 to the agency’s Armstrong Flight Research Center for a two-day event highlighting the ways NASA is with you when you fly. The NASA social gave participants an exclusive look at the latest tools and technologies being developed to improve the efficiency, safety and adaptability of air transportation. Also, Next ISS crew trains, 3D printer installed in space, Asteroid capture technology test, Journey to Mars media day and more!

NWRA AVOSS Wake Vortex Prediction Algorithm. 3.1.1

NASA Technical Reports Server (NTRS)

Robins, R. E.; Delisi, D. P.; Hinton, David (Technical Monitor)

2002-01-01

This report provides a detailed description of the wake vortex prediction algorithm used in the Demonstration Version of NASA's Aircraft Vortex Spacing System (AVOSS). The report includes all equations used in the algorithm, an explanation of how to run the algorithm, and a discussion of how the source code for the algorithm is organized. Several appendices contain important supplementary information, including suggestions for enhancing the algorithm and results from test cases.

The architecture of adaptive neural network based on a fuzzy inference system for implementing intelligent control in photovoltaic systems

NASA Astrophysics Data System (ADS)

Gimazov, R.; Shidlovskiy, S.

2018-05-01

In this paper, we consider the architecture of the algorithm for extreme regulation in the photovoltaic system. An algorithm based on an adaptive neural network with fuzzy inference is proposed. The implementation of such an algorithm not only allows solving a number of problems in existing algorithms for extreme power regulation of photovoltaic systems, but also creates a reserve for the creation of a universal control system for a photovoltaic system.

Adaptable Binary Programs

DTIC Science & Technology

1994-04-01

a variation of Ziv - Lempel compression [ZL77]. We found that using a standard compression algorithm rather than semantic compression allowed simplified...mentation. In Proceedings of the Conference on Programming Language Design and Implementation, 1993. (ZL77] J. Ziv and A. Lempel . A universal algorithm ...required by adaptable binaries. Our ABS stores adaptable binary information using the conventional binary symbol table and compresses this data using

Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Stein, G.; Pratt, S. G.

1979-01-01

The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

Mouse EEG spike detection based on the adapted continuous wavelet transform

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.

2016-04-01

Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Recent Results from NASA's Morphing Project

NASA Technical Reports Server (NTRS)

McGowan, Anna-Maria R.; Washburn, Anthony E.; Horta, Lucas G.; Bryant, Robert G.; Cox, David E.; Siochi, Emilie J.; Padula, Sharon L.; Holloway, Nancy M.

2002-01-01

The NASA Morphing Project seeks to develop and assess advanced technologies and integrated component concepts to enable efficient, multi-point adaptability in air and space vehicles. In the context of the project, the word "morphing" is defined as "efficient, multi-point adaptability" and may include macro, micro, structural and/or fluidic approaches. The project includes research on smart materials, adaptive structures, micro flow control, biomimetic concepts, optimization and controls. This paper presents an updated overview of the content of the Morphing Project including highlights of recent research results.

Multigrid solution of internal flows using unstructured solution adaptive meshes

NASA Technical Reports Server (NTRS)

Smith, Wayne A.; Blake, Kenneth R.

1992-01-01

This is the final report of the NASA Lewis SBIR Phase 2 Contract Number NAS3-25785, Multigrid Solution of Internal Flows Using Unstructured Solution Adaptive Meshes. The objective of this project, as described in the Statement of Work, is to develop and deliver to NASA a general three-dimensional Navier-Stokes code using unstructured solution-adaptive meshes for accuracy and multigrid techniques for convergence acceleration. The code will primarily be applied, but not necessarily limited, to high speed internal flows in turbomachinery.

High-Speed On-Board Data Processing Platform for LIDAR Projects at NASA Langley Research Center

NASA Astrophysics Data System (ADS)

Beyon, J.; Ng, T. K.; Davis, M. J.; Adams, J. K.; Lin, B.

2015-12-01

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program during April, 2012 - April, 2015. HOPS is an enabler for science missions with extremely high data processing rates. In this three-year effort of HOPS, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) and 3-D Winds were of interest in particular. As for ASCENDS, HOPS replaces time domain data processing with frequency domain processing while making the real-time on-board data processing possible. As for 3-D Winds, HOPS offers real-time high-resolution wind profiling with 4,096-point fast Fourier transform (FFT). HOPS is adaptable with quick turn-around time. Since HOPS offers reusable user-friendly computational elements, its FPGA IP Core can be modified for a shorter development period if the algorithm changes. The FPGA and memory bandwidth of HOPS is 20 GB/sec while the typical maximum processor-to-SDRAM bandwidth of the commercial radiation tolerant high-end processors is about 130-150 MB/sec. The inter-board communication bandwidth of HOPS is 4 GB/sec while the effective processor-to-cPCI bandwidth of commercial radiation tolerant high-end boards is about 50-75 MB/sec. Also, HOPS offers VHDL cores for the easy and efficient implementation of ASCENDS and 3-D Winds, and other similar algorithms. A general overview of the 3-year development of HOPS is the goal of this presentation.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Attitude determination and calibration using a recursive maximum likelihood-based adaptive Kalman filter

NASA Technical Reports Server (NTRS)

Kelly, D. A.; Fermelia, A.; Lee, G. K. F.

1990-01-01

An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

PubMed Central

Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah

2015-01-01

A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974

Climate Change Adaptation Science Activities at NASA Johnson Space Center

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Lulla, Kamlesh

2012-01-01

The Johnson Space Center (JSC), located in the southeast metropolitan region of Houston, TX is the prime NASA center for human spaceflight operations and astronaut training, but it also houses the unique collection of returned extraterrestrial samples, including lunar samples from the Apollo missions. The Center's location adjacent to Clear Lake and the Clear Creek watershed, an estuary of Galveston Bay, puts it at direct annual risk from hurricanes, but also from a number of other climate-related hazards including drought, floods, sea level rise, heat waves, and high wind events all assigned Threat Levels of 2 or 3 in the most recent NASA Center Disaster/Risk Matrix produced by the Climate Adaptation Science Investigator Working Group. Based on prior CASI workshops at other NASA centers, it is recognized that JSC is highly vulnerable to climate-change related hazards and has a need for adaptation strategies. We will present an overview of prior CASI-related work at JSC, including publication of a climate change and adaptation informational data brochure, and a Resilience and Adaptation to Climate Risks Workshop that was held at JSC in early March 2012. Major outcomes of that workshop that form a basis for work going forward are 1) a realization that JSC is embedded in a regional environmental and social context, and that potential climate change effects and adaptation strategies will not, and should not, be constrained by the Center fence line; 2) a desire to coordinate data collection and adaptation planning activities with interested stakeholders to form a regional climate change adaptation center that could facilitate interaction with CASI; 3) recognition that there is a wide array of basic data (remotely sensed, in situ, GIS/mapping, and historical) available through JSC and other stakeholders, but this data is not yet centrally accessible for planning purposes.

An adaptive grid algorithm for one-dimensional nonlinear equations

NASA Technical Reports Server (NTRS)

Gutierrez, William E.; Hills, Richard G.

1990-01-01

Richards' equation, which models the flow of liquid through unsaturated porous media, is highly nonlinear and difficult to solve. Step gradients in the field variables require the use of fine grids and small time step sizes. The numerical instabilities caused by the nonlinearities often require the use of iterative methods such as Picard or Newton interation. These difficulties result in large CPU requirements in solving Richards equation. With this in mind, adaptive and multigrid methods are investigated for use with nonlinear equations such as Richards' equation. Attention is focused on one-dimensional transient problems. To investigate the use of multigrid and adaptive grid methods, a series of problems are studied. First, a multigrid program is developed and used to solve an ordinary differential equation, demonstrating the efficiency with which low and high frequency errors are smoothed out. The multigrid algorithm and an adaptive grid algorithm is used to solve one-dimensional transient partial differential equations, such as the diffusive and convective-diffusion equations. The performance of these programs are compared to that of the Gauss-Seidel and tridiagonal methods. The adaptive and multigrid schemes outperformed the Gauss-Seidel algorithm, but were not as fast as the tridiagonal method. The adaptive grid scheme solved the problems slightly faster than the multigrid method. To solve nonlinear problems, Picard iterations are introduced into the adaptive grid and tridiagonal methods. Burgers' equation is used as a test problem for the two algorithms. Both methods obtain solutions of comparable accuracy for similar time increments. For the Burgers' equation, the adaptive grid method finds the solution approximately three times faster than the tridiagonal method. Finally, both schemes are used to solve the water content formulation of the Richards' equation. For this problem, the adaptive grid method obtains a more accurate solution in fewer work units and less computation time than required by the tridiagonal method. The performance of the adaptive grid method tends to degrade as the solution process proceeds in time, but still remains faster than the tridiagonal scheme.

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Zhu, Feng; Ukkusuri, Satish V.

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better atmore » higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2, NO x, VOC, PM 10) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.« less

An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

PubMed

Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

2015-10-21

To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

PubMed

Huang, X N; Ren, H P

2016-05-13

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation.

Adaptive fuzzy system for 3-D vision

NASA Technical Reports Server (NTRS)

Mitra, Sunanda

1993-01-01

An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

Intelligent Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

NASA Technical Reports Server (NTRS)

Hunter, H. E.

1972-01-01

The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

A selective-update affine projection algorithm with selective input vectors

NASA Astrophysics Data System (ADS)

Kong, NamWoong; Shin, JaeWook; Park, PooGyeon

2011-10-01

This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.

Analysis of convergence of an evolutionary algorithm with self-adaptation using a stochastic Lyapunov function.

PubMed

Semenov, Mikhail A; Terkel, Dmitri A

2003-01-01

This paper analyses the convergence of evolutionary algorithms using a technique which is based on a stochastic Lyapunov function and developed within the martingale theory. This technique is used to investigate the convergence of a simple evolutionary algorithm with self-adaptation, which contains two types of parameters: fitness parameters, belonging to the domain of the objective function; and control parameters, responsible for the variation of fitness parameters. Although both parameters mutate randomly and independently, they converge to the "optimum" due to the direct (for fitness parameters) and indirect (for control parameters) selection. We show that the convergence velocity of the evolutionary algorithm with self-adaptation is asymptotically exponential, similar to the velocity of the optimal deterministic algorithm on the class of unimodal functions. Although some martingale inequalities have not be proved analytically, they have been numerically validated with 0.999 confidence using Monte-Carlo simulations.

A NASA/University Joint Venture in Space Science (JOVE)

NASA Technical Reports Server (NTRS)

Vaughn, Danny M.

1997-01-01

Several papers have been given to national level meeting and a paper has been published in an international journal. Several additional papers have been co-author by students. The initial research project on the Atchafalaya Delta seems to have died in part due to a transfer of the NASA colleague to another location and subsequent reassigment to another job title. I have continued to include credit to NASA for many of my papers presented and published: A major debris flow along the Wasatch front in Northern Ogden; Spatial and volumetric changes in the Atchafalaya delta, Louisiana; An analysis of prehistoric Greenstone artifact in northern Alabama; An assessment of surfacing algorithm; Analysis of georeferencing algorithms to assess spatial accuracy.

Self-Avoiding Walks Over Adaptive Triangular Grids

NASA Technical Reports Server (NTRS)

Heber, Gerd; Biswas, Rupak; Gao, Guang R.; Saini, Subhash (Technical Monitor)

1999-01-01

Space-filling curves is a popular approach based on a geometric embedding for linearizing computational meshes. We present a new O(n log n) combinatorial algorithm for constructing a self avoiding walk through a two dimensional mesh containing n triangles. We show that for hierarchical adaptive meshes, the algorithm can be locally adapted and easily parallelized by taking advantage of the regularity of the refinement rules. The proposed approach should be very useful in the runtime partitioning and load balancing of adaptive unstructured grids.

Arbitrary-level hanging nodes for adaptive hphp-FEM approximations in 3D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavel Kus; Pavel Solin; David Andrs

2014-11-01

In this paper we discuss constrained approximation with arbitrary-level hanging nodes in adaptive higher-order finite element methods (hphp-FEM) for three-dimensional problems. This technique enables using highly irregular meshes, and it greatly simplifies the design of adaptive algorithms as it prevents refinements from propagating recursively through the finite element mesh. The technique makes it possible to design efficient adaptive algorithms for purely hexahedral meshes. We present a detailed mathematical description of the method and illustrate it with numerical examples.

Approach for Structurally Clearing an Adaptive Compliant Trailing Edge Flap for Flight

NASA Technical Reports Server (NTRS)

Miller, Eric J.; Lokos, William A.; Cruz, Josue; Crampton, Glen; Stephens, Craig A.; Kota, Sridhar; Ervin, Gregory; Flick, Pete

2015-01-01

The Adaptive Compliant Trailing Edge (ACTE) flap was flown on the NASA Gulfstream GIII test bed at the NASA Armstrong Flight Research Center. This smoothly curving flap replaced the existing Fowler flaps creating a seamless control surface. This compliant structure, developed by FlexSys Inc. in partnership with Air Force Research Laboratory, supported NASA objectives for airframe structural noise reduction, aerodynamic efficiency, and wing weight reduction through gust load alleviation. A thorough structures airworthiness approach was developed to move this project safely to flight.

Finding Blackbody Temperature and Emissivity on a Sub-Pixel Scale

NASA Astrophysics Data System (ADS)

Bernstein, D. J.; Bausell, J.; Grigsby, S.; Kudela, R. M.

2015-12-01

Surface temperature and emissivity provide important insight into the ecosystem being remotely sensed. Dozier (1981) proposed a an algorithm to solve for percent coverage and temperatures of two different surface types (e.g. sea surface, cloud cover, etc.) within a given pixel, with a constant value for emissivity assumed. Here we build on Dozier (1981) by proposing an algorithm that solves for both temperature and emissivity of a water body within a satellite pixel by assuming known percent coverage of surface types within the pixel. Our algorithm generates thermal infrared (TIR) and emissivity end-member spectra for the two surface types. Our algorithm then superposes these end-member spectra on emissivity and TIR spectra emitted from four pixels with varying percent coverage of different surface types. The algorithm was tested preliminarily (48 iterations) using simulated pixels containing more than one surface type, with temperature and emissivity percent errors of ranging from 0 to 1.071% and 2.516 to 15.311% respectively[1]. We then tested the algorithm using a MASTER image from MASTER collected as part of the NASA Student Airborne Research Program (NASA SARP). Here the temperature of water was calculated to be within 0.22 K of in situ data. The algorithm calculated emissivity of water with an accuracy of 0.13 to 1.53% error for Salton Sea pixels collected with MASTER, also collected as part of NASA SARP. This method could improve retrievals for the HyspIRI sensor. [1] Percent error for emissivity was generated by averaging percent error across all selected bands widths.

Improved OMI Nitrogen Dioxide Retrievals Aided by NASA's A-Train High-Resolution Data

NASA Astrophysics Data System (ADS)

Lamsal, L. N.; Krotkov, N. A.; Vasilkov, A. P.; Marchenko, S. V.; Qin, W.; Yang, E. S.; Fasnacht, Z.; Haffner, D. P.; Swartz, W. H.; Spurr, R. J. D.; Joiner, J.

2017-12-01

Space-based global observation of nitrogen dioxide (NO2) is among the main objectives of the NASA Aura Ozone Monitoring Instrument (OMI) mission, aimed at advancing our understanding of the sources and trends of nitrogen oxides (NOx). These applications benefit from improved retrieval techniques and enhancement in data quality. Here, we describe our recent and planned updates to the NASA OMI standard NO2 products. The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major changes include (1) improvements in spectral fitting algorithms for NO2 and cloud, (2) improved information in the vertical distribution of NO2, and (3) use of geometry-dependent surface reflectivity information derived from NASA's Aqua MODIS over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. These algorithm updates, which lead to more accurate tropospheric NO2 retrievals from OMI, are relevant for other past, contemporary, and future satellite instruments.

An adaptive tracker for ShipIR/NTCS

NASA Astrophysics Data System (ADS)

Ramaswamy, Srinivasan; Vaitekunas, David A.

2015-05-01

A key component in any image-based tracking system is the adaptive tracking algorithm used to segment the image into potential targets, rank-and-select the best candidate target, and the gating of the selected target to further improve tracker performance. This paper will describe a new adaptive tracker algorithm added to the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR). The new adaptive tracking algorithm is an optional feature used with any of the existing internal NTCS or user-defined seeker algorithms (e.g., binary centroid, intensity centroid, and threshold intensity centroid). The algorithm segments the detected pixels into clusters, and the smallest set of clusters that meet the detection criterion is obtained by using a knapsack algorithm to identify the set of clusters that should not be used. The rectangular area containing the chosen clusters defines an inner boundary, from which a weighted centroid is calculated as the aim-point. A track-gate is then positioned around the clusters, taking into account the rate of change of the bounding area and compensating for any gimbal displacement. A sequence of scenarios is used to test the new tracking algorithm on a generic unclassified DDG ShipIR model, with and without flares, and demonstrate how some of the key seeker signals are impacted by both the ship and flare intrinsic signatures.

Asian dust aerosol: Optical effect on satellite ocean color signal and a scheme of its correction

NASA Astrophysics Data System (ADS)

Fukushima, H.; Toratani, M.

1997-07-01

The paper first exhibits the influence of the Asian dust aerosol (KOSA) on a coastal zone color scanner (CZCS) image which records erroneously low or negative satellite-derived water-leaving radiance especially in a shorter wavelength region. This suggests the presence of spectrally dependent absorption which was disregarded in the past atmospheric correction algorithms. On the basis of the analysis of the scene, a semiempirical optical model of the Asian dust aerosol that relates aerosol single scattering albedo (ωA) to the spectral ratio of aerosol optical thickness between 550 nm and 670 nm is developed. Then, as a modification to a standard CZCS atmospheric correction algorithm (NASA standard algorithm), a scheme which estimates pixel-wise aerosol optical thickness, and in turn ωA, is proposed. The assumption of constant normalized water-leaving radiance at 550 nm is adopted together with a model of aerosol scattering phase function. The scheme is combined to the standard algorithm, performing atmospheric correction just the same as the standard version with a fixed Angstrom coefficient except in the case where the presence of Asian dust aerosol is detected by the lowered satellite-derived Angstrom exponent. Some of the model parameter values are determined so that the scheme does not produce any spatial discontinuity with the standard scheme. The algorithm was tested against the Japanese Asian dust CZCS scene with parameter values of the spectral dependency of ωA, first statistically determined and second optimized for selected pixels. Analysis suggests that the parameter values depend on the assumed Angstrom coefficient for standard algorithm, at the same time defining the spatial extent of the area to apply the Asian dust scheme. The algorithm was also tested for a Saharan dust scene, showing the relevance of the scheme but with different parameter setting. Finally, the algorithm was applied to a data set of 25 CZCS scenes to produce a monthly composite of pigment concentration for April 1981. Through these analyses, the modified algorithm is considered robust in the sense that it operates most compatibly with the standard algorithm yet performs adaptively in response to the magnitude of the dust effect.

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus

2014-01-01

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

A Demons algorithm for image registration with locally adaptive regularization.

PubMed

Cahill, Nathan D; Noble, J Alison; Hawkes, David J

2009-01-01

Thirion's Demons is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.

Fast ℓ1-regularized space-time adaptive processing using alternating direction method of multipliers

NASA Astrophysics Data System (ADS)

Qin, Lilong; Wu, Manqing; Wang, Xuan; Dong, Zhen

2017-04-01

Motivated by the sparsity of filter coefficients in full-dimension space-time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-to-clutter-noise ratio performance than other algorithms.

Development of model reference adaptive control theory for electric power plant control applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mabius, L.E.

1982-09-15

The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis.more » An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.« less

Assessment of Cognitive Communications Interest Areas for NASA Needs and Benefits

NASA Technical Reports Server (NTRS)

Knoblock, Eric J.; Madanayake, Arjuna

2017-01-01

This effort provides a survey and assessment of various cognitive communications interest areas, including node-to-node link optimization, intelligent routing/networking, and learning algorithms, and is conducted primarily from the perspective of NASA space communications needs and benefits. Areas of consideration include optimization methods, learning algorithms, and candidate implementations/technologies. Assessments of current research efforts are provided with mention of areas for further investment. Other considerations, such as antenna technologies and cognitive radio platforms, are briefly provided as well.

Pre-Launch Evaluation of the NPP VIIRS Land and Cryosphere EDRs to Meet NASA's Science Requirements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Justice, Chris; Csiszar, Ivan; Key, Jeffrey R.; Devadiga, Sadashiva; Davidson, carol; Wolfe, Robert; Privette, Jeff

2011-01-01

This paper summarizes the NASA Visible Infrared Imaging Radiometer Suite (VIIRS) Land Science team's findings to date with respect to the utility of the VIIRS Land and Cryosphere EDRs to meet NASA's science requirements. Based on previous assessments and results from a recent 51-day global test performed by the Land Product Evaluation and Analysis Tool Element (Land PEATE), the NASA VIIRS Land Science team has determined that, if all the Land and Cryosphere EDRs are to serve the needs of the science community, a number of changes to several products and the Interface Data Processing Segment (IDPS) algorithm processing chain will be needed. In addition, other products will also need to be added to the VIIRS Land product suite to provide continuity for all of the MODIS land data record. As the NASA research program explores new global change research areas, the VIIRS instrument should also provide the polar-orbiting imager data from which new algorithms could be developed, produced, and validated.

Adaptive protection algorithm and system

DOEpatents

Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

2009-04-28

An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

Mexico Fires

Atmospheric Science Data Center

2013-04-18

... on the right. This quantity is retrieved using an automated computer algorithm that takes advantage of MISR's multi-angle capability. Areas ... NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed ...

Real-Gas Flow Properties for NASA Langley Research Center Aerothermodynamic Facilities Complex Wind Tunnels

NASA Technical Reports Server (NTRS)

Hollis, Brian R.

1996-01-01

A computational algorithm has been developed which can be employed to determine the flow properties of an arbitrary real (virial) gas in a wind tunnel. A multiple-coefficient virial gas equation of state and the assumption of isentropic flow are used to model the gas and to compute flow properties throughout the wind tunnel. This algorithm has been used to calculate flow properties for the wind tunnels of the Aerothermodynamics Facilities Complex at the NASA Langley Research Center, in which air, CF4. He, and N2 are employed as test gases. The algorithm is detailed in this paper and sample results are presented for each of the Aerothermodynamic Facilities Complex wind tunnels.

Local flow management/profile descent algorithm. Fuel-efficient, time-controlled profiles for the NASA TSRV airplane

NASA Technical Reports Server (NTRS)

Groce, J. L.; Izumi, K. H.; Markham, C. H.; Schwab, R. W.; Thompson, J. L.

1986-01-01

The Local Flow Management/Profile Descent (LFM/PD) algorithm designed for the NASA Transport System Research Vehicle program is described. The algorithm provides fuel-efficient altitude and airspeed profiles consistent with ATC restrictions in a time-based metering environment over a fixed ground track. The model design constraints include accommodation of both published profile descent procedures and unpublished profile descents, incorporation of fuel efficiency as a flight profile criterion, operation within the performance capabilities of the Boeing 737-100 airplane with JT8D-7 engines, and conformity to standard air traffic navigation and control procedures. Holding and path stretching capabilities are included for long delay situations.

Mapping and Assessing Variability in the Antarctic Marginal Ice Zone, the Pack Ice and Coastal Polynyas

NASA Astrophysics Data System (ADS)

Stroeve, Julienne; Jenouvrier, Stephanie

2016-04-01

Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore mapping their spatial extent, seasonal and interannual variability is essential for understanding how current and future changes in these biological active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of different ice types to the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent data record for assessing different ice types. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depends strongly on what sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Polynya area is also larger in the NASA Team algorithm, and the timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.

Software Testbed for Developing and Evaluating Integrated Autonomous Systems

DTIC Science & Technology

2015-03-01

EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to...using the Internet Communications Engine ( ICE ), an object-oriented toolkit for building distributed applications. TABLE OF CONTENTS 1...ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA???s EUROPA planning system for plan generation. The adaptive

An Adaptive Cultural Algorithm with Improved Quantum-behaved Particle Swarm Optimization for Sonar Image Detection.

PubMed

Wang, Xingmei; Hao, Wenqian; Li, Qiming

2017-12-18

This paper proposes an adaptive cultural algorithm with improved quantum-behaved particle swarm optimization (ACA-IQPSO) to detect the underwater sonar image. In the population space, to improve searching ability of particles, iterative times and the fitness value of particles are regarded as factors to adaptively adjust the contraction-expansion coefficient of the quantum-behaved particle swarm optimization algorithm (QPSO). The improved quantum-behaved particle swarm optimization algorithm (IQPSO) can make particles adjust their behaviours according to their quality. In the belief space, a new update strategy is adopted to update cultural individuals according to the idea of the update strategy in shuffled frog leaping algorithm (SFLA). Moreover, to enhance the utilization of information in the population space and belief space, accept function and influence function are redesigned in the new communication protocol. The experimental results show that ACA-IQPSO can obtain good clustering centres according to the grey distribution information of underwater sonar images, and accurately complete underwater objects detection. Compared with other algorithms, the proposed ACA-IQPSO has good effectiveness, excellent adaptability, a powerful searching ability and high convergence efficiency. Meanwhile, the experimental results of the benchmark functions can further demonstrate that the proposed ACA-IQPSO has better searching ability, convergence efficiency and stability.

Wireless rake-receiver using adaptive filter with a family of partial update algorithms in noise cancellation applications

NASA Astrophysics Data System (ADS)

Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Aldhaibani, Jaafar A.; Salman, M. K.; Abdullah, Farah Salwani

2015-05-01

For high data rate propagation in wireless ultra-wideband (UWB) communication systems, the inter-symbol interference (ISI), multiple-access interference (MAI), and multiple-users interference (MUI) are influencing the performance of the wireless systems. In this paper, the rake-receiver was presented with the spread signal by direct sequence spread spectrum (DS-SS) technique. The adaptive rake-receiver structure was shown with adjusting the receiver tap weights using least mean squares (LMS), normalized least mean squares (NLMS), and affine projection algorithms (APA) to support the weak signals by noise cancellation and mitigate the interferences. To minimize the data convergence speed and to reduce the computational complexity by the previous algorithms, a well-known approach of partial-updates (PU) adaptive filters were employed with algorithms, such as sequential-partial, periodic-partial, M-max-partial, and selective-partial updates (SPU) in the proposed system. The simulation results of bit error rate (BER) versus signal-to-noise ratio (SNR) are illustrated to show the performance of partial-update algorithms that have nearly comparable performance with the full update adaptive filters. Furthermore, the SPU-partial has closed performance to the full-NLMS and full-APA while the M-max-partial has closed performance to the full-LMS updates algorithms.

Noise-shaping gradient descent-based online adaptation algorithms for digital calibration of analog circuits.

PubMed

Chakrabartty, Shantanu; Shaga, Ravi K; Aono, Kenji

2013-04-01

Analog circuits that are calibrated using digital-to-analog converters (DACs) use a digital signal processor-based algorithm for real-time adaptation and programming of system parameters. In this paper, we first show that this conventional framework for adaptation yields suboptimal calibration properties because of artifacts introduced by quantization noise. We then propose a novel online stochastic optimization algorithm called noise-shaping or ΣΔ gradient descent, which can shape the quantization noise out of the frequency regions spanning the parameter adaptation trajectories. As a result, the proposed algorithms demonstrate superior parameter search properties compared to floating-point gradient methods and better convergence properties than conventional quantized gradient-methods. In the second part of this paper, we apply the ΣΔ gradient descent algorithm to two examples of real-time digital calibration: 1) balancing and tracking of bias currents, and 2) frequency calibration of a band-pass Gm-C biquad filter biased in weak inversion. For each of these examples, the circuits have been prototyped in a 0.5-μm complementary metal-oxide-semiconductor process, and we demonstrate that the proposed algorithm is able to find the optimal solution even in the presence of spurious local minima, which are introduced by the nonlinear and non-monotonic response of calibration DACs.

A fast 4D cone beam CT reconstruction method based on the OSC-TV algorithm.

PubMed

Mascolo-Fortin, Julia; Matenine, Dmitri; Archambault, Louis; Després, Philippe

2018-01-01

Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.

Benefit of adaptive FEC in shared backup path protected elastic optical network.

PubMed

Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

2015-07-27

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

A Piloted Evaluation of Damage Accommodating Flight Control Using a Remotely Piloted Vehicle

NASA Technical Reports Server (NTRS)

Cunningham, Kevin; Cox, David E.; Murri, Daniel G.; Riddick, Stephen E.

2011-01-01

Toward the goal of reducing the fatal accident rate of large transport airplanes due to loss of control, the NASA Aviation Safety Program has conducted research into flight control technologies that can provide resilient control of airplanes under adverse flight conditions, including damage and failure. As part of the safety program s Integrated Resilient Aircraft Control Project, the NASA Airborne Subscale Transport Aircraft Research system was designed to address the challenges associated with the safe and efficient subscale flight testing of research control laws under adverse flight conditions. This paper presents the results of a series of pilot evaluations of several flight control algorithms used during an offset-to-landing task conducted at altitude. The purpose of this investigation was to assess the ability of various flight control technologies to prevent loss of control as stability and control characteristics were degraded. During the course of 8 research flights, data were recorded while one task was repeatedly executed by a single evaluation pilot. Two generic failures, which degraded stability and control characteristics, were simulated inflight for each of the 9 different flight control laws that were tested. The flight control laws included three different adaptive control methodologies, several linear multivariable designs, a linear robust design, a linear stability augmentation system, and a direct open-loop control mode. Based on pilot Cooper-Harper Ratings obtained for this test, the adaptive flight control laws provided the greatest overall benefit for the stability and control degradation scenarios that were considered. Also, all controllers tested provided a significant improvement in handling qualities over the direct open-loop control mode.

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

NASA Technical Reports Server (NTRS)

Zhu, Zhifan; Jung, Yoon; Lee, Hanbong; Schier, Sebastian; Okuniek, Nikolai; Gerdes, Ingrid

2016-01-01

In this work, fast-time simulations have been conducted using SARDA tools at Hamburg airport by NASA and real-time simulations using CADEO and TRACC with the NLR ATM Research Simulator (NARSIM) by DLR. The outputs are analyzed using a set of common metrics collaborated between DLR and NASA. The proposed metrics are derived from International Civil Aviation Organization (ICAO)s Key Performance Areas (KPAs) in capability, efficiency, predictability and environment, and adapted to simulation studies. The results are examined to explore and compare the merits and shortcomings of the two approaches using the common performance metrics. Particular attention is paid to the concept of the close-loop, trajectory-based taxi as well as the application of US concept to the European airport. Both teams consider the trajectory-based surface operation concept a critical technology advance in not only addressing the current surface traffic management problems, but also having potential application in unmanned vehicle maneuver on airport surface, such as autonomous towing or TaxiBot [6][7] and even Remote Piloted Aircraft (RPA). Based on this work, a future integration of TRACC and SOSS is described aiming at bringing conflict-free trajectory-based operation concept to US airport.

An Adaptive Immune Genetic Algorithm for Edge Detection

NASA Astrophysics Data System (ADS)

Li, Ying; Bai, Bendu; Zhang, Yanning

An adaptive immune genetic algorithm (AIGA) based on cost minimization technique method for edge detection is proposed. The proposed AIGA recommends the use of adaptive probabilities of crossover, mutation and immune operation, and a geometric annealing schedule in immune operator to realize the twin goals of maintaining diversity in the population and sustaining the fast convergence rate in solving the complex problems such as edge detection. Furthermore, AIGA can effectively exploit some prior knowledge and information of the local edge structure in the edge image to make vaccines, which results in much better local search ability of AIGA than that of the canonical genetic algorithm. Experimental results on gray-scale images show the proposed algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.

Adaptive Mesh Refinement in Curvilinear Body-Fitted Grid Systems

NASA Technical Reports Server (NTRS)

Steinthorsson, Erlendur; Modiano, David; Colella, Phillip

1995-01-01

To be truly compatible with structured grids, an AMR algorithm should employ a block structure for the refined grids to allow flow solvers to take advantage of the strengths of unstructured grid systems, such as efficient solution algorithms for implicit discretizations and multigrid schemes. One such algorithm, the AMR algorithm of Berger and Colella, has been applied to and adapted for use with body-fitted structured grid systems. Results are presented for a transonic flow over a NACA0012 airfoil (AGARD-03 test case) and a reflection of a shock over a double wedge.

Sinogram-based adaptive iterative reconstruction for sparse view x-ray computed tomography

NASA Astrophysics Data System (ADS)

Trinca, D.; Zhong, Y.; Wang, Y.-Z.; Mamyrbayev, T.; Libin, E.

2016-10-01

With the availability of more powerful computing processors, iterative reconstruction algorithms have recently been successfully implemented as an approach to achieving significant dose reduction in X-ray CT. In this paper, we propose an adaptive iterative reconstruction algorithm for X-ray CT, that is shown to provide results comparable to those obtained by proprietary algorithms, both in terms of reconstruction accuracy and execution time. The proposed algorithm is thus provided for free to the scientific community, for regular use, and for possible further optimization.

An adaptive bit synchronization algorithm under time-varying environment.

NASA Technical Reports Server (NTRS)

Chow, L. R.; Owen, H. A., Jr.; Wang, P. P.

1973-01-01

This paper presents an adaptive estimation algorithm for bit synchronization, assuming that the parameters of the incoming data process are time-varying. Experiment results have proved that this synchronizer is workable either judged by the amount of data required or the speed of convergence.

Absolute phase estimation: adaptive local denoising and global unwrapping.

PubMed

Bioucas-Dias, Jose; Katkovnik, Vladimir; Astola, Jaakko; Egiazarian, Karen

2008-10-10

The paper attacks absolute phase estimation with a two-step approach: the first step applies an adaptive local denoising scheme to the modulo-2 pi noisy phase; the second step applies a robust phase unwrapping algorithm to the denoised modulo-2 pi phase obtained in the first step. The adaptive local modulo-2 pi phase denoising is a new algorithm based on local polynomial approximations. The zero-order and the first-order approximations of the phase are calculated in sliding windows of varying size. The zero-order approximation is used for pointwise adaptive window size selection, whereas the first-order approximation is used to filter the phase in the obtained windows. For phase unwrapping, we apply the recently introduced robust (in the sense of discontinuity preserving) PUMA unwrapping algorithm [IEEE Trans. Image Process.16, 698 (2007)] to the denoised wrapped phase. Simulations give evidence that the proposed algorithm yields state-of-the-art performance, enabling strong noise attenuation while preserving image details. (c) 2008 Optical Society of America

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation.

PubMed

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-09-05

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation

PubMed Central

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-01-01

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes. PMID:28872629

Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm

NASA Technical Reports Server (NTRS)

Shapiro, Jerome M.; Martucci, Stephen A.; Czigler, Martin

1994-01-01

The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.

A Data System for a Rapid Evaluation Class of Subscale Aerial Vehicle

NASA Technical Reports Server (NTRS)

Hogge, Edward F.; Quach, Cuong C.; Vazquez, Sixto L.; Hill, Boyd L.

2011-01-01

A low cost, rapid evaluation, test aircraft is used to develop and test airframe damage diagnosis algorithms at Langley Research Center as part of NASA's Aviation Safety Program. The remotely operated subscale aircraft is instrumented with sensors to monitor structural response during flight. Data is collected for good and compromised airframe configurations to develop data driven models for diagnosing airframe state. This paper describes the data acquisition system (DAS) of the rapid evaluation test aircraft. A PC/104 form factor DAS was developed to allow use of Matlab, Simulink simulation code in Langley's existing subscale aircraft flight test infrastructure. The small scale of the test aircraft permitted laboratory testing of the actual flight article under controlled conditions. The low cost and modularity of the DAS permitted adaptation to various flight experiment requirements.

Automated Data Processing as an AI Planning Problem

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wanlin; Nemani, Ramakrishna; Votava, Petr

2003-01-01

NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.

Evaluation of the effect of vibration nonlinearity on convergence behavior of adaptive higher harmonic controllers

NASA Technical Reports Server (NTRS)

Molusis, J. A.; Mookerjee, P.; Bar-Shalom, Y.

1983-01-01

Effect of nonlinearity on convergence of the local linear and global linear adaptive controllers is evaluated. A nonlinear helicopter vibration model is selected for the evaluation which has sufficient nonlinearity, including multiple minimum, to assess the vibration reduction capability of the adaptive controllers. The adaptive control algorithms are based upon a linear transfer matrix assumption and the presence of nonlinearity has a significant effect on algorithm behavior. Simulation results are presented which demonstrate the importance of the caution property in the global linear controller. Caution is represented by a time varying rate weighting term in the local linear controller and this improves the algorithm convergence. Nonlinearity in some cases causes Kalman filter divergence. Two forms of the Kalman filter covariance equation are investigated.

Advances in Adaptive Control Methods

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2009-01-01

This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

Wind tunnel wall interference investigations in NAE/NRC High Reynolds Number 2D Facility and NASA Langley 0.3m Transonic Cryogenic Tunnel

NASA Technical Reports Server (NTRS)

Chan, Y. Y.; Nishimura, Y.; Mineck, R. E.

1989-01-01

Results are reported from a NAE/NRC and NASA cooperative program on two-dimensional wind-tunnel wall-interference research, aimed at developing the technology for correcting or eliminating wall interference effects in two-dimensional transonic wind-tunnel investigations. Both NASA Langley and NAE facilities are described, along with a NASA-designed and fabricated airfoil model. It is shown that data from the NAE facility, corrected for wall interference, agree with those obtained from the NASA tunnel, which has adaptive walls; the comparison of surface pressure data shows that the flowfield conditions in which the model is investigated appear to be nearly identical under most conditions. It is concluded that both approaches, posttest correction and an adaptive wall, adequately eliminate the tunnel-wall interference effects.

Low complexity Reed-Solomon-based low-density parity-check design for software defined optical transmission system based on adaptive puncturing decoding algorithm

NASA Astrophysics Data System (ADS)

Pan, Xiaolong; Liu, Bo; Zheng, Jianglong; Tian, Qinghua

2016-08-01

We propose and demonstrate a low complexity Reed-Solomon-based low-density parity-check (RS-LDPC) code with adaptive puncturing decoding algorithm for elastic optical transmission system. Partial received codes and the relevant column in parity-check matrix can be punctured to reduce the calculation complexity by adaptive parity-check matrix during decoding process. The results show that the complexity of the proposed decoding algorithm is reduced by 30% compared with the regular RS-LDPC system. The optimized code rate of the RS-LDPC code can be obtained after five times iteration.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Low-cost Tools for Aerial Video Geolocation and Air Traffic Analysis for Delay Reduction Using Google Earth

NASA Astrophysics Data System (ADS)

Zetterlind, V.; Pledgie, S.

2009-12-01

Low-cost, low-latency, robust geolocation and display of aerial video is a common need for a wide range of earth observing as well as emergency response and security applications. While hardware costs for aerial video collection systems, GPS, and inertial sensors have been decreasing, software costs for geolocation algorithms and reference imagery/DTED remain expensive and highly proprietary. As part of a Federal Small Business Innovative Research project, MosaicATM and EarthNC, Inc have developed a simple geolocation system based on the Google Earth API and Google's 'built-in' DTED and reference imagery libraries. This system geolocates aerial video based on platform and camera position, attitude, and field-of-view metadata using geometric photogrammetric principles of ray-intersection with DTED. Geolocated video can be directly rectified and viewed in the Google Earth API during processing. Work is underway to extend our geolocation code to NASA World Wind for additional flexibility and a fully open-source platform. In addition to our airborne remote sensing work, MosaicATM has developed the Surface Operations Data Analysis and Adaptation (SODAA) tool, funded by NASA Ames, which supports analysis of airport surface operations to optimize aircraft movements and reduce fuel burn and delays. As part of SODAA, MosaicATM and EarthNC, Inc have developed powerful tools to display national airspace data and time-animated 3D flight tracks in Google Earth for 4D analysis. The SODAA tool can convert raw format flight track data, FAA National Flight Data (NFD), and FAA 'Adaptation' airport surface data to a spatial database representation and then to Google Earth KML. The SODAA client provides users with a simple graphical interface through which to generate queries with a wide range of predefined and custom filters, plot results, and export for playback in Google Earth in conjunction with NFD and Adaptation overlays.

INITIAL APPL;ICATION OF THE ADAPTIVE GRID AIR POLLUTION MODEL

EPA Science Inventory

The paper discusses an adaptive-grid algorithm used in air pollution models. The algorithm reduces errors related to insufficient grid resolution by automatically refining the grid scales in regions of high interest. Meanwhile the grid scales are coarsened in other parts of the d...

Adaptive geodesic transform for segmentation of vertebrae on CT images

NASA Astrophysics Data System (ADS)

Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

2014-03-01

Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sideris, Michael G.

2017-09-01

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63-84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10-30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.

On recursive least-squares filtering algorithms and implementations. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hsieh, Shih-Fu

1990-01-01

In many real-time signal processing applications, fast and numerically stable algorithms for solving least-squares problems are necessary and important. In particular, under non-stationary conditions, these algorithms must be able to adapt themselves to reflect the changes in the system and take appropriate adjustments to achieve optimum performances. Among existing algorithms, the QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective for adaptive signal processing. In order to increase the speed of processing and achieve high throughput rate, many algorithms are being vectorized and/or pipelined to facilitate high degrees of parallelism. A time-recursive formulation of RLS filtering employing block QRD will be considered first. Several methods, including a new non-continuous windowing scheme based on selectively rejecting contaminated data, were investigated for adaptive processing. Based on systolic triarrays, many other forms of systolic arrays are shown to be capable of implementing different algorithms. Various updating and downdating systolic algorithms and architectures for RLS filtering are examined and compared in details, which include Householder reflector, Gram-Schmidt procedure, and Givens rotation. A unified approach encompassing existing square-root-free algorithms is also proposed. For the sinusoidal spectrum estimation problem, a judicious method of separating the noise from the signal is of great interest. Various truncated QR methods are proposed for this purpose and compared to the truncated SVD method. Computer simulations provided for detailed comparisons show the effectiveness of these methods. This thesis deals with fundamental issues of numerical stability, computational efficiency, adaptivity, and VLSI implementation for the RLS filtering problems. In all, various new and modified algorithms and architectures are proposed and analyzed; the significance of any of the new method depends crucially on specific application.

Active Control of Wind Tunnel Noise

NASA Technical Reports Server (NTRS)

Hollis, Patrick (Principal Investigator)

1991-01-01

The need for an adaptive active control system was realized, since a wind tunnel is subjected to variations in air velocity, temperature, air turbulence, and some other factors such as nonlinearity. Among many adaptive algorithms, the Least Mean Squares (LMS) algorithm, which is the simplest one, has been used in an Active Noise Control (ANC) system by some researchers. However, Eriksson's results, Eriksson (1985), showed instability in the ANC system with an ER filter for random noise input. The Restricted Least Squares (RLS) algorithm, although computationally more complex than the LMS algorithm, has better convergence and stability properties. The ANC system in the present work was simulated by using an FIR filter with an RLS algorithm for different inputs and for a number of plant models. Simulation results for the ANC system with acoustic feedback showed better robustness when used with the RLS algorithm than with the LMS algorithm for all types of inputs. Overall attenuation in the frequency domain was better in the case of the RLS adaptive algorithm. Simulation results with a more realistic plant model and an RLS adaptive algorithm showed a slower convergence rate than the case with an acoustic plant as a delay plant. However, the attenuation properties were satisfactory for the simulated system with the modified plant. The effect of filter length on the rate of convergence and attenuation was studied. It was found that the rate of convergence decreases with increase in filter length, whereas the attenuation increases with increase in filter length. The final design of the ANC system was simulated and found to have a reasonable convergence rate and good attenuation properties for an input containing discrete frequencies and random noise.

Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.

PubMed

Wang, Changqing; Zhang, Xinyuan; Liu, Xiaoyun; He, Taigang; Chen, Wufan; Feng, Qianjin; Feng, Yanqiu

2018-08-01

To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med 80:792-801, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Comparison of Reconstruction and Control algorithms on the ESO end-to-end simulator OCTOPUS

NASA Astrophysics Data System (ADS)

Montilla, I.; Béchet, C.; Lelouarn, M.; Correia, C.; Tallon, M.; Reyes, M.; Thiébaut, É.

Extremely Large Telescopes are very challenging concerning their Adaptive Optics requirements. Their diameters, the specifications demanded by the science for which they are being designed for, and the planned use of Extreme Adaptive Optics systems, imply a huge increment in the number of degrees of freedom in the deformable mirrors. It is necessary to study new reconstruction algorithms to implement the real time control in Adaptive Optics at the required speed. We have studied the performance, applied to the case of the European ELT, of three different algorithms: the matrix-vector multiplication (MVM) algorithm, considered as a reference; the Fractal Iterative Method (FrIM); and the Fourier Transform Reconstructor (FTR). The algorithms have been tested on ESO's OCTOPUS software, which simulates the atmosphere, the deformable mirror, the sensor and the closed-loop control. The MVM is the default reconstruction and control method implemented in OCTOPUS, but it scales in O(N2) operations per loop so it is not considered as a fast algorithm for wave-front reconstruction and control on an Extremely Large Telescope. The two other methods are the fast algorithms studied in the E-ELT Design Study. The performance, as well as their response in the presence of noise and with various atmospheric conditions, has been compared using a Single Conjugate Adaptive Optics configuration for a 42 m diameter ELT, with a total amount of 5402 actuators. Those comparisons made on a common simulator allow to enhance the pros and cons of the various methods, and give us a better understanding of the type of reconstruction algorithm that an ELT demands.

An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)

PubMed Central

2011-01-01

Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. PMID:21952080

Online adaptive neural control of a robotic lower limb prosthesis

NASA Astrophysics Data System (ADS)

Spanias, J. A.; Simon, A. M.; Finucane, S. B.; Perreault, E. J.; Hargrove, L. J.

2018-02-01

Objective. The purpose of this study was to develop and evaluate an adaptive intent recognition algorithm that continuously learns to incorporate a lower limb amputee’s neural information (acquired via electromyography (EMG)) as they ambulate with a robotic leg prosthesis. Approach. We present a powered lower limb prosthesis that was configured to acquire the user’s neural information and kinetic/kinematic information from embedded mechanical sensors, and identify and respond to the user’s intent. We conducted an experiment with eight transfemoral amputees over multiple days. EMG and mechanical sensor data were collected while subjects using a powered knee/ankle prosthesis completed various ambulation activities such as walking on level ground, stairs, and ramps. Our adaptive intent recognition algorithm automatically transitioned the prosthesis into the different locomotion modes and continuously updated the user’s model of neural data during ambulation. Main results. Our proposed algorithm accurately and consistently identified the user’s intent over multiple days, despite changing neural signals. The algorithm incorporated 96.31% [0.91%] (mean, [standard error]) of neural information across multiple experimental sessions, and outperformed non-adaptive versions of our algorithm—with a 6.66% [3.16%] relative decrease in error rate. Significance. This study demonstrates that our adaptive intent recognition algorithm enables incorporation of neural information over long periods of use, allowing assistive robotic devices to accurately respond to the user’s intent with low error rates.

Current Status of Japanese Global Precipitation Measurement (GPM) Research Project

NASA Astrophysics Data System (ADS)

Kachi, Misako; Oki, Riko; Kubota, Takuji; Masaki, Takeshi; Kida, Satoshi; Iguchi, Toshio; Nakamura, Kenji; Takayabu, Yukari N.

2013-04-01

The Global Precipitation Measurement (GPM) mission is a mission led by the Japan Aerospace Exploration Agency (JAXA) and the National Aeronautics and Space Administration (NASA) under collaboration with many international partners, who will provide constellation of satellites carrying microwave radiometer instruments. The GPM Core Observatory, which carries the Dual-frequency Precipitation Radar (DPR) developed by JAXA and the National Institute of Information and Communications Technology (NICT), and the GPM Microwave Imager (GMI) developed by NASA. The GPM Core Observatory is scheduled to be launched in early 2014. JAXA also provides the Global Change Observation Mission (GCOM) 1st - Water (GCOM-W1) named "SHIZUKU," as one of constellation satellites. The SHIZUKU satellite was launched in 18 May, 2012 from JAXA's Tanegashima Space Center, and public data release of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the SHIZUKU satellite was planned that Level 1 products in January 2013, and Level 2 products including precipitation in May 2013. The Japanese GPM research project conducts scientific activities on algorithm development, ground validation, application research including production of research products. In addition, we promote collaboration studies in Japan and Asian countries, and public relations activities to extend potential users of satellite precipitation products. In pre-launch phase, most of our activities are focused on the algorithm development and the ground validation related to the algorithm development. As the GPM standard products, JAXA develops the DPR Level 1 algorithm, and the NASA-JAXA Joint Algorithm Team develops the DPR Level 2 and the DPR-GMI combined Level2 algorithms. JAXA also develops the Global Rainfall Map product as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. All standard algorithms including Japan-US joint algorithm will be reviewed by the Japan-US Joint Precipitation Measuring Mission (PMM) Science Team (JPST) before the release. DPR Level 2 algorithm has been developing by the DPR Algorithm Team led by Japan, which is under the NASA-JAXA Joint Algorithm Team. The Level-2 algorithms will provide KuPR only products, KaPR only products, and Dual-frequency Precipitation products, with estimated precipitation rate, radar reflectivity, and precipitation information such as drop size distribution and bright band height. At-launch code was developed in December 2012. In addition, JAXA and NASA have provided synthetic DPR L1 data and tests have been performed using them. Japanese Global Rainfall Map algorithm for the GPM mission has been developed by the Global Rainfall Map Algorithm Development Team in Japan. The algorithm succeeded heritages of the Global Satellite Mapping for Precipitation (GSMaP) project, which was sponsored by the Japan Science and Technology Agency (JST) under the Core Research for Evolutional Science and Technology (CREST) framework between 2002 and 2007. The GSMaP near-real-time version and reanalysis version have been in operation at JAXA, and browse images and binary data available at the GSMaP web site (http://sharaku.eorc.jaxa.jp/GSMaP/). The GSMaP algorithm for GPM is developed in collaboration with AMSR2 standard algorithm for precipitation product, and their validation studies are closely related. As JAXA GPM product, we will provide 0.1-degree grid and hourly product for standard and near-realtime processing. Outputs will include hourly rainfall, gauge-calibrated hourly rainfall, and several quality information (satellite information flag, time information flag, and gauge quality information) over global areas from 60°S to 60°N. At-launch code of GSMaP for GPM is under development, and will be delivered to JAXA GPM Mission Operation System by April 2013. At-launch code will include several updates of microwave imager and sounder algorithms and databases, and introduction of rain-gauge correction.

Some design guidelines for discrete-time adaptive controllers

NASA Technical Reports Server (NTRS)

Rohrs, C. E.; Athans, M.; Valavani, L.; Stein, G.

1985-01-01

There have been many algorithms proposed for adaptive control which will provide globally asymptotically stable controllers if some stringent conditions on the plant are met. The conditions on the plant cannot be met in practice as all plants will contain high frequency unmolded dynamics therefore, blind implementation of the published algorithms can lead to disastrous results. This paper uses a linearization analysis of a non-linear adaptive controller to demonstrate analytically design guidelines which aleviate some of the problems associated with adaptive control in the presence of unmodeled dynamics.

STAR adaptation of QR algorithm. [program for solving over-determined systems of linear equations

NASA Technical Reports Server (NTRS)

Shah, S. N.

1981-01-01

The QR algorithm used on a serial computer and executed on the Control Data Corporation 6000 Computer was adapted to execute efficiently on the Control Data STAR-100 computer. How the scalar program was adapted for the STAR-100 and why these adaptations yielded an efficient STAR program is described. Program listings of the old scalar version and the vectorized SL/1 version are presented in the appendices. Execution times for the two versions applied to the same system of linear equations, are compared.

Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

PubMed Central

2012-01-01

Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II

PubMed Central

Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg Y.; Fernández, Eduardo

2010-01-01

In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate. PMID:22315579

Implementation of a Wavefront-Sensing Algorithm

NASA Technical Reports Server (NTRS)

Smith, Jeffrey S.; Dean, Bruce; Aronstein, David

2013-01-01

A computer program has been written as a unique implementation of an image-based wavefront-sensing algorithm reported in "Iterative-Transform Phase Retrieval Using Adaptive Diversity" (GSC-14879-1), NASA Tech Briefs, Vol. 31, No. 4 (April 2007), page 32. This software was originally intended for application to the James Webb Space Telescope, but is also applicable to other segmented-mirror telescopes. The software is capable of determining optical-wavefront information using, as input, a variable number of irradiance measurements collected in defocus planes about the best focal position. The software also uses input of the geometrical definition of the telescope exit pupil (otherwise denoted the pupil mask) to identify the locations of the segments of the primary telescope mirror. From the irradiance data and mask information, the software calculates an estimate of the optical wavefront (a measure of performance) of the telescope generally and across each primary mirror segment specifically. The software is capable of generating irradiance data, wavefront estimates, and basis functions for the full telescope and for each primary-mirror segment. Optionally, each of these pieces of information can be measured or computed outside of the software and incorporated during execution of the software.

NASA Tech Briefs, March 2005

NASA Technical Reports Server (NTRS)

2005-01-01

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.

The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space

NASA Technical Reports Server (NTRS)

Palm, Stephen P.; Hlavka, Dennis; Hart, Bill; Welton, E. Judd; Spinhirne, James

2000-01-01

The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Adaptive algorithm of magnetic heading detection

NASA Astrophysics Data System (ADS)

Liu, Gong-Xu; Shi, Ling-Feng

2017-11-01

Magnetic data obtained from a magnetic sensor usually fluctuate in a certain range, which makes it difficult to estimate the magnetic heading accurately. In fact, magnetic heading information is usually submerged in noise because of all kinds of electromagnetic interference and the diversity of the pedestrian’s motion states. In order to solve this problem, a new adaptive algorithm based on the (typically) right-angled corridors of a building or residential buildings is put forward to process heading information. First, a 3D indoor localization platform is set up based on MPU9250. Then, several groups of data are measured by changing the experimental environment and pedestrian’s motion pace. The raw data from the attached inertial measurement unit are calibrated and arranged into a time-stamped array and written to a data file. Later, the data file is imported into MATLAB for processing and analysis using the proposed adaptive algorithm. Finally, the algorithm is verified by comparison with the existing algorithm. The experimental results show that the algorithm has strong robustness and good fault tolerance, which can detect the heading information accurately and in real-time.

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

PubMed

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.

PubMed

Jiang, Wen Jun; Wittek, Peter; Zhao, Li; Gao, Shi Chao

2014-01-01

Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. The new feature enables real-time adaptive waveform detection using an algorithm of linear time complexity. It can also recognize notches in the waveform and it is inherently robust to baseline drift. An implementation of the algorithm on Android is available for free download. We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.

Research on adaptive optics image restoration algorithm based on improved joint maximum a posteriori method

NASA Astrophysics Data System (ADS)

Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying

2018-03-01

In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.

Hyperspectral data acquisition and analysis in imaging and real-time active MIR backscattering spectroscopy

NASA Astrophysics Data System (ADS)

Jarvis, Jan; Haertelt, Marko; Hugger, Stefan; Butschek, Lorenz; Fuchs, Frank; Ostendorf, Ralf; Wagner, Joachim; Beyerer, Juergen

2017-04-01

In this work we present data analysis algorithms for detection of hazardous substances in hyperspectral observations acquired using active mid-infrared (MIR) backscattering spectroscopy. We present a novel background extraction algorithm based on the adaptive target generation process proposed by Ren and Chang called the adaptive background generation process (ABGP) that generates a robust and physically meaningful set of background spectra for operation of the well-known adaptive matched subspace detection (AMSD) algorithm. It is shown that the resulting AMSD-ABGP detection algorithm competes well with other widely used detection algorithms. The method is demonstrated in measurement data obtained by two fundamentally different active MIR hyperspectral data acquisition devices. A hyperspectral image sensor applicable in static scenes takes a wavelength sequential approach to hyperspectral data acquisition, whereas a rapid wavelength-scanning single-element detector variant of the same principle uses spatial scanning to generate the hyperspectral observation. It is shown that the measurement timescale of the latter is sufficient for the application of the data analysis algorithms even in dynamic scenarios.

Automatic motor task selection via a bandit algorithm for a brain-controlled button

NASA Astrophysics Data System (ADS)

Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

A heuristic re-mapping algorithm reducing inter-level communication in SAMR applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steensland, Johan; Ray, Jaideep

2003-07-01

This paper aims at decreasing execution time for large-scale structured adaptive mesh refinement (SAMR) applications by proposing a new heuristic re-mapping algorithm and experimentally showing its effectiveness in reducing inter-level communication. Tests were done for five different SAMR applications. The overall goal is to engineer a dynamically adaptive meta-partitioner capable of selecting and configuring the most appropriate partitioning strategy at run-time based on current system and application state. Such a metapartitioner can significantly reduce execution times for general SAMR applications. Computer simulations of physical phenomena are becoming increasingly popular as they constitute an important complement to real-life testing. In manymore » cases, such simulations are based on solving partial differential equations by numerical methods. Adaptive methods are crucial to efficiently utilize computer resources such as memory and CPU. But even with adaption, the simulations are computationally demanding and yield huge data sets. Thus parallelization and the efficient partitioning of data become issues of utmost importance. Adaption causes the workload to change dynamically, calling for dynamic (re-) partitioning to maintain efficient resource utilization. The proposed heuristic algorithm reduced inter-level communication substantially. Since the complexity of the proposed algorithm is low, this decrease comes at a relatively low cost. As a consequence, we draw the conclusion that the proposed re-mapping algorithm would be useful to lower overall execution times for many large SAMR applications. Due to its usefulness and its parameterization, the proposed algorithm would constitute a natural and important component of the meta-partitioner.« less

A hand tracking algorithm with particle filter and improved GVF snake model

NASA Astrophysics Data System (ADS)

Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

2017-07-01

To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

Adaptively resizing populations: Algorithm, analysis, and first results

NASA Technical Reports Server (NTRS)

Smith, Robert E.; Smuda, Ellen

1993-01-01

Deciding on an appropriate population size for a given Genetic Algorithm (GA) application can often be critical to the algorithm's success. Too small, and the GA can fall victim to sampling error, affecting the efficacy of its search. Too large, and the GA wastes computational resources. Although advice exists for sizing GA populations, much of this advice involves theoretical aspects that are not accessible to the novice user. An algorithm for adaptively resizing GA populations is suggested. This algorithm is based on recent theoretical developments that relate population size to schema fitness variance. The suggested algorithm is developed theoretically, and simulated with expected value equations. The algorithm is then tested on a problem where population sizing can mislead the GA. The work presented suggests that the population sizing algorithm may be a viable way to eliminate the population sizing decision from the application of GA's.

Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

NASA Technical Reports Server (NTRS)

Folta, David C.; Hawkins, Albin; Bauer, Frank H. (Technical Monitor)

2001-01-01

NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Guidance, Navigation, and Control center at the Goddard Space Flight Center (GSFC) implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm and the onboard flight design and presents the validation results of this unique system. Results from functionality assessment through fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(tm), its ground-based predecessor, and a standalone algorithm.

Redundancy management for efficient fault recovery in NASA's distributed computing system

NASA Technical Reports Server (NTRS)

Malek, Miroslaw; Pandya, Mihir; Yau, Kitty

1991-01-01

The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance.

Adaptive-gain fast super-twisting sliding mode fault tolerant control for a reusable launch vehicle in reentry phase.

PubMed

Zhang, Yao; Tang, Shengjing; Guo, Jie

2017-11-01

In this paper, a novel adaptive-gain fast super-twisting (AGFST) sliding mode attitude control synthesis is carried out for a reusable launch vehicle subject to actuator faults and unknown disturbances. According to the fast nonsingular terminal sliding mode surface (FNTSMS) and adaptive-gain fast super-twisting algorithm, an adaptive fault tolerant control law for the attitude stabilization is derived to protect against the actuator faults and unknown uncertainties. Firstly, a second-order nonlinear control-oriented model for the RLV is established by feedback linearization method. And on the basis a fast nonsingular terminal sliding mode (FNTSM) manifold is designed, which provides fast finite-time global convergence and avoids singularity problem as well as chattering phenomenon. Based on the merits of the standard super-twisting (ST) algorithm and fast reaching law with adaption, a novel adaptive-gain fast super-twisting (AGFST) algorithm is proposed for the finite-time fault tolerant attitude control problem of the RLV without any knowledge of the bounds of uncertainties and actuator faults. The important feature of the AGFST algorithm includes non-overestimating the values of the control gains and faster convergence speed than the standard ST algorithm. A formal proof of the finite-time stability of the closed-loop system is derived using the Lyapunov function technique. An estimation of the convergence time and accurate expression of convergence region are also provided. Finally, simulations are presented to illustrate the effectiveness and superiority of the proposed control scheme. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Performance study of LMS based adaptive algorithms for unknown system identification

NASA Astrophysics Data System (ADS)

Javed, Shazia; Ahmad, Noor Atinah

2014-07-01

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

NASA Astrophysics Data System (ADS)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

An improved self-adaptive ant colony algorithm based on genetic strategy for the traveling salesman problem

NASA Astrophysics Data System (ADS)

Wang, Pan; Zhang, Yi; Yan, Dong

2018-05-01

Ant Colony Algorithm (ACA) is a powerful and effective algorithm for solving the combination optimization problem. Moreover, it was successfully used in traveling salesman problem (TSP). But it is easy to prematurely converge to the non-global optimal solution and the calculation time is too long. To overcome those shortcomings, a new method is presented-An improved self-adaptive Ant Colony Algorithm based on genetic strategy. The proposed method adopts adaptive strategy to adjust the parameters dynamically. And new crossover operation and inversion operation in genetic strategy was used in this method. We also make an experiment using the well-known data in TSPLIB. The experiment results show that the performance of the proposed method is better than the basic Ant Colony Algorithm and some improved ACA in both the result and the convergence time. The numerical results obtained also show that the proposed optimization method can achieve results close to the theoretical best known solutions at present.

Performance study of LMS based adaptive algorithms for unknown system identification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Javed, Shazia; Ahmad, Noor Atinah

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signalmore » is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.« less

Real-Time Adaptive Control of Flow-Induced Cavity Tones

NASA Technical Reports Server (NTRS)

Kegerise, Michael A.; Cabell, Randolph H.; Cattafesta, Louis N.

2004-01-01

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. The adaptive control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. The algorithm was also able t o maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are colocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible. In the control-algorithm development, the cavity dynamics are treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support this treatment.

Analysis of Online DBA Algorithm with Adaptive Sleep Cycle in WDM EPON

NASA Astrophysics Data System (ADS)

Pajčin, Bojan; Matavulj, Petar; Radivojević, Mirjana

2018-05-01

In order to manage Quality of Service (QoS) and energy efficiency in the optical access network, an online Dynamic Bandwidth Allocation (DBA) algorithm with adaptive sleep cycle is presented. This DBA algorithm has the ability to allocate an additional bandwidth to the end user within a single sleep cycle whose duration changes depending on the current buffers occupancy. The purpose of this DBA algorithm is to tune the duration of the sleep cycle depending on the network load in order to provide service to the end user without violating strict QoS requests in all network operating conditions.

NOVA: A new multi-level logic simulator

NASA Technical Reports Server (NTRS)

Miles, L.; Prins, P.; Cameron, K.; Shovic, J.

1990-01-01

A new logic simulator that was developed at the NASA Space Engineering Research Center for VLSI Design was described. The simulator is multi-level, being able to simulate from the switch level through the functional model level. NOVA is currently in the Beta test phase and was used to simulate chips designed for the NASA Space Station and the Explorer missions. A new algorithm was devised to simulate bi-directional pass transistors and a preliminary version of the algorithm is presented. The usage of functional models in NOVA is also described and performance figures are presented.

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

Proceedings of the Conference on Moments and Signal

NASA Astrophysics Data System (ADS)

Purdue, P.; Solomon, H.

1992-09-01

The focus of this paper is (1) to describe systematic methodologies for selecting nonlinear transformations for blind equalization algorithms (and thus new types of cumulants), and (2) to give an overview of the existing blind equalization algorithms and point out their strengths as well as weaknesses. It is shown that all blind equalization algorithms belong in one of the following three categories, depending where the nonlinear transformation is being applied on the data: (1) the Bussgang algorithms, where the nonlinearity is in the output of the adaptive equalization filter; (2) the polyspectra (or Higher-Order Spectra) algorithms, where the nonlinearity is in the input of the adaptive equalization filter; and (3) the algorithms where the nonlinearity is inside the adaptive filter, i.e., the nonlinear filter or neural network. We describe methodologies for selecting nonlinear transformations based on various optimality criteria such as MSE or MAP. We illustrate that such existing algorithms as Sato, Benveniste-Goursat, Godard or CMA, Stop-and-Go, and Donoho are indeed special cases of the Bussgang family of techniques when the nonlinearity is memoryless. We present results that demonstrate the polyspectra-based algorithms exhibit faster convergence rate than Bussgang algorithms. However, this improved performance is at the expense of more computations per iteration. We also show that blind equalizers based on nonlinear filters or neural networks are more suited for channels that have nonlinear distortions.

A tunable algorithm for collective decision-making.

PubMed

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Model reference adaptive control of robots

NASA Technical Reports Server (NTRS)

Steinvorth, Rodrigo

1991-01-01

This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.

OAI and NASA's Scientific and Technical Information.

ERIC Educational Resources Information Center

Nelson, Michael L.; Rocker, JoAnne; Harrison, Terry L.

2003-01-01

Details NASA's (National Aeronautics & Space Administration (USA)) involvement in defining and testing the Open Archives Initiative (OAI) Protocol for Metadata Harvesting (OAI-PMH) and experience with adapting existing NASA distributed searching DLs (digital libraries) to use the OAI-PMH and metadata harvesting. Discusses some new digital…

Standardizing Interfaces for External Access to Data and Processing for the NASA Ozone Product Evaluation and Test Element (PEATE)

NASA Technical Reports Server (NTRS)

Tilmes, Curt A.; Fleig, Albert J.

2008-01-01

NASA's traditional science data processing systems have focused on specific missions, and providing data access, processing and services to the funded science teams of those specific missions. Recently NASA has been modifying this stance, changing the focus from Missions to Measurements. Where a specific Mission has a discrete beginning and end, the Measurement considers long term data continuity across multiple missions. Total Column Ozone, a critical measurement of atmospheric composition, has been monitored for'decades on a series of Total Ozone Mapping Spectrometer (TOMS) instruments. Some important European missions also monitor ozone, including the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY. With the U.S.IEuropean cooperative launch of the Dutch Ozone Monitoring Instrument (OMI) on NASA Aura satellite, and the GOME-2 instrumental on MetOp, the ozone monitoring record has been further extended. In conjunction with the U.S. Department of Defense (DoD) and the National Oceanic and Atmospheric Administration (NOAA), NASA is now preparing to evaluate data and algorithms for the next generation Ozone Mapping and Profiler Suite (OMPS) which will launch on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in 2010. NASA is constructing the Science Data Segment (SDS) which is comprised of several elements to evaluate the various NPP data products and algorithms. The NPP SDS Ozone Product Evaluation and Test Element (PEATE) will build on the heritage of the TOMS and OM1 mission based processing systems. The overall measurement based system that will encompass these efforts is the Atmospheric Composition Processing System (ACPS). We have extended the system to include access to publically available data sets from other instruments where feasible, including non-NASA missions as appropriate. The heritage system was largely monolithic providing a very controlled processing flow from data.ingest of satellite data to the ultimate archive of specific operational data products. The ACPS allows more open access with standard protocols including HTTP, SOAPIXML, RSS and various REST incarnations. External entities can be granted access to various modules within the system, including an extended data archive, metadata searching, production planning and processing. Data access is provided with very fine grained access control. It is possible to easily designate certain datasets as being available to the public, or restricted to groups of researchers, or limited strictly to the originator. This can be used, for example, to release one's best validated data to the public, but restrict the "new version" of data processed with a new, unproven algorithm until it is ready. Similarly, the system can provide access to algorithms, both as modifiable source code (where possible) and fully integrated executable Algorithm Plugin Packages (APPs). This enables researchers to download publically released versions of the processing algorithms and easily reproduce the processing remotely, while interacting with the ACPS. The algorithms can be modified allowing better experimentation and rapid improvement. The modified algorithms can be easily integrated back into the production system for large scale bulk processing to evaluate improvements. The system includes complete provenance tracking of algorithms, data and the entire processing environment. The origin of any data or algorithms is recorded and the entire history of the processing chains are stored such that a researcher can understand the entire data flow. Provenance is captured in a form suitable for the system to guarantee scientific reproducability of any data product it distributes even in cases where the physical data products themselves have been deleted due to space constraints. We are currently working on Semantic Web ontologies for representing the various provenance information. A new web site focusing on consolidating informaon about the measurement, processing system, and data access has been established to encourage interaction with the overall scientific community. We will describe the system, its data processing capabilities, and the methods the community can use to interact with the standard interfaces of the system.

Indirect learning control for nonlinear dynamical systems

NASA Technical Reports Server (NTRS)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Johnson, Marcus; Nguyen, Nhan

2011-01-01

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

An adaptive DPCM algorithm for predicting contours in NTSC composite video signals

NASA Astrophysics Data System (ADS)

Cox, N. R.

An adaptive DPCM algorithm is proposed for encoding digitized National Television Systems Committee (NTSC) color video signals. This algorithm essentially predicts picture contours in the composite signal without resorting to component separation. The contour parameters (slope thresholds) are optimized using four 'typical' television frames that have been sampled at three times the color subcarrier frequency. Three variations of the basic predictor are simulated and compared quantitatively with three non-adaptive predictors of similar complexity. By incorporating a dual-word-length coder and buffer memory, high quality color pictures can be encoded at 4.0 bits/pel or 42.95 Mbit/s. The effect of channel error propagation is also investigated.

Novel medical image enhancement algorithms

NASA Astrophysics Data System (ADS)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Improvement and implementation for Canny edge detection algorithm

NASA Astrophysics Data System (ADS)

Yang, Tao; Qiu, Yue-hong

2015-07-01

Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.

Studying NASA's Transition to Ka-Band Communications for Low Earth Orbit

NASA Technical Reports Server (NTRS)

Chelmins, David; Reinhart, Richard; Mortensen, Dale; Welch, Bryan; Downey, Joseph; Evans, Mike

2014-01-01

As the S-band spectrum becomes crowded, future space missions will need to consider moving command and telemetry services to Ka-band. NASAs Space Communications and Navigation (SCaN) Testbed provides a software-defined radio (SDR) platform that is capable of supporting investigation of this service transition. The testbed contains two S-band SDRs and one Ka-band SDR. Over the past year, SCaN Testbed has demonstrated Ka-band communications capabilities with NASAs Tracking and Data Relay Satellite System (TDRSS) using both open- and closed-loop antenna tracking profiles. A number of technical areas need to be addressed for successful transition to Ka-band. The smaller antenna beamwidth at Ka-band increases the criticality of antenna pointing, necessitating closed loop tracking algorithms and new techniques for received power estimation. Additionally, the antenna pointing routines require enhanced knowledge of spacecraft position and attitude for initial acquisition, versus an S-band antenna. Ka-band provides a number of technical advantages for bulk data transfer. Unlike at S-band, a larger bandwidth may be available for space missions, allowing increased data rates. The potential for high rate data transfer can also be extended for direct-to-ground links through use of variable or adaptive coding and modulation. Specific examples of Ka-band research from SCaN Testbeds first year of operation will be cited, such as communications link performance with TDRSS, and the effects of truss flexure on antenna pointing.

Studying NASA's Transition to Ka-Band Communications for Low Earth Orbit

NASA Technical Reports Server (NTRS)

Chelmins, David T.; Reinhart, Richard C.; Mortensen, Dale; Welch, Bryan; Downey, Joseph; Evans, Michael

2014-01-01

As the S-band spectrum becomes crowded, future space missions will need to consider moving command and telemetry services to Ka-band. NASA's Space Communications and Navigation (SCaN) Testbed provides a software-defined radio (SDR) platform that is capable of supporting investigation of this service transition. The testbed contains two S-band SDRs and one Ka-band SDR. Over the past year, SCaN Testbed has demonstrated Ka-band communications capabilities with NASAs Tracking and Data Relay Satellite System (TDRSS) using both open- and closed-loop antenna tracking profiles. A number of technical areas need to be addressed for successful transition to Ka-band. The smaller antenna beamwidth at Ka-band increases the criticality of antenna pointing, necessitating closed loop tracking algorithms and new techniques for received power estimation. Additionally, the antenna pointing routines require enhanced knowledge of spacecraft position and attitude for initial acquisition, versus an S-band antenna. Ka-band provides a number of technical advantages for bulk data transfer. Unlike at S-band, a larger bandwidth may be available for space missions, allowing increased data rates. The potential for high rate data transfer can also be extended for direct-to-ground links through use of variable or adaptive coding and modulation. Specific examples of Ka-band research from SCaN Testbeds first year of operation will be cited, such as communications link performance with TDRSS, and the effects of truss flexure on antenna pointing.

Space Launch System Resource Reel 2017

NASA Image and Video Library

2017-12-01

NASA's new heavy-lift rocket, the Space Launch System, will be the most powerful rocket every built, launching astronauts in NASA's Orion spacecraft on missions into deep space. Two solid rocket boosters and four RS-25 engines will power the massive rocket, providing 8 million pounds of thrust during launch. Production and testing are underway for much of the rocket's critical hardware. With major welding complete on core stage hardware for the first integrated flight of SLS and Orion, the liquid hydrogen tank, intertank and liquid oxygen tank are ready for further outfitting. NASA's barge Pegasus has transported test hardware the first SLS hardware, the engine section to NASA's Marshall Space Flight Center in Huntsville, Alabama, for testing. In preparation for testing and handling operations, engineers have built the core stage pathfinder, to practice transport without the risk of damaging flight hardware. Integrated structural testing is complete on the top part of the rocket, including the Orion stage adapter, launch vehicle stage adapter and interim cryogenic propulsion stage. The Orion Stage Adapter for SLS's first flight, which will carry 13 CubeSats as secondary payloads, is ready to be outfitted with wiring and brackets. Once structural testing and flight hardware production are complete, the core stage will undergo "green run" testing in the B-2 test stand at NASA's Stennis Space Center in Bay St. Louis, Mississippi. For more information about SLS, visit nasa.gov/sls.

Suomi NPP VIIRS Ocean Color Data Product Early Mission Assessment

NASA Technical Reports Server (NTRS)

Turpie, Kevin R.; Robinson, Wayne D.; Franz, Bryan A.; Eplee, Robert E., Jr.; Meister, Gerhard; Fireman, Gwyn F.; Patt, Frederick S.; Barnes, Robert A.; McClain, Charles R.

2013-01-01

Following the launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polarorbiting Partnership (NPP) spacecraft, the NASA NPP VIIRS Ocean Science Team (VOST) began an evaluation of ocean color data products to determine whether they could continue the existing NASA ocean color climate data record (CDR). The VOST developed an independent evaluation product based on NASA algorithms with a reprocessing capability. Here we present a preliminary assessment of both the operational ocean color data products and the NASA evaluation data products regarding their applicability to NASA science objectives.

Modeling, Control, and Estimation of Flexible, Aerodynamic Structures

NASA Astrophysics Data System (ADS)

Ray, Cody W.

Engineers have long been inspired by nature’s flyers. Such animals navigate complex environments gracefully and efficiently by using a variety of evolutionary adaptations for high-performance flight. Biologists have discovered a variety of sensory adaptations that provide flow state feedback and allow flying animals to feel their way through flight. A specialized skeletal wing structure and plethora of robust, adaptable sensory systems together allow nature’s flyers to adapt to myriad flight conditions and regimes. In this work, motivated by biology and the successes of bio-inspired, engineered aerial vehicles, linear quadratic control of a flexible, morphing wing design is investigated, helping to pave the way for truly autonomous, mission-adaptive craft. The proposed control algorithm is demonstrated to morph a wing into desired positions. Furthermore, motivated specifically by the sensory adaptations organisms possess, this work transitions to an investigation of aircraft wing load identification using structural response as measured by distributed sensors. A novel, recursive estimation algorithm is utilized to recursively solve the inverse problem of load identification, providing both wing structural and aerodynamic states for use in a feedback control, mission-adaptive framework. The recursive load identification algorithm is demonstrated to provide accurate load estimate in both simulation and experiment.

An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU

PubMed Central

Xu, Hailong; Cui, Xiaowei; Lu, Mingquan

2016-01-01

Nowadays, software-defined radio (SDR) has become a common approach to evaluate new algorithms. However, in the field of Global Navigation Satellite System (GNSS) adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability. In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU) are documented. This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance. Both Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP) are implemented with a wide range of parameters. Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode. To fully take advantage of the parallelism resource provided by the GPU, a batched method in programming is proposed. Tests and experiments are conducted to evaluate both the computational and anti-jamming performance. This platform can be used for research and prototyping, as well as a real product in certain applications. PMID:26978363

An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU.

PubMed

Xu, Hailong; Cui, Xiaowei; Lu, Mingquan

2016-03-11

Nowadays, software-defined radio (SDR) has become a common approach to evaluate new algorithms. However, in the field of Global Navigation Satellite System (GNSS) adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability. In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU) are documented. This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance. Both Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP) are implemented with a wide range of parameters. Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode. To fully take advantage of the parallelism resource provided by the GPU, a batched method in programming is proposed. Tests and experiments are conducted to evaluate both the computational and anti-jamming performance. This platform can be used for research and prototyping, as well as a real product in certain applications.

Dynamic grid refinement for partial differential equations on parallel computers

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids to provide adaptive resolution and fast solution of PDEs. An asynchronous version of FAC, called AFAC, that completely eliminates the bottleneck to parallelism is presented. This paper describes the advantage that this algorithm has in adaptive refinement for moving singularities on multiprocessor computers. This work is applicable to the parallel solution of two- and three-dimensional shock tracking problems.

Performance comparisons on spatial lattice algorithm and direct matrix inverse method with application to adaptive arrays processing

NASA Technical Reports Server (NTRS)

An, S. H.; Yao, K.

1986-01-01

Lattice algorithm has been employed in numerous adaptive filtering applications such as speech analysis/synthesis, noise canceling, spectral analysis, and channel equalization. In this paper the application to adaptive-array processing is discussed. The advantages are fast convergence rate as well as computational accuracy independent of the noise and interference conditions. The results produced by this technique are compared to those obtained by the direct matrix inverse method.

Adaption of unstructured meshes using node movement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carpenter, J.G.; McRae, V.D.S.

1996-12-31

The adaption algorithm of Benson and McRae is modified for application to unstructured grids. The weight function generation was modified for application to unstructured grids and movement was limited to prevent cross over. A NACA 0012 airfoil is used as a test case to evaluate the modified algorithm when applied to unstructured grids and compared to results obtained by Warren. An adaptive mesh solution for the Sudhoo and Hall four element airfoil is included as a demonstration case.

Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

NASA Technical Reports Server (NTRS)

Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.

1985-01-01

This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

Fuzzy-TLX: using fuzzy integrals for evaluating human mental workload with NASA-Task Load indeX in laboratory and field studies.

PubMed

Mouzé-Amady, Marc; Raufaste, Eric; Prade, Henri; Meyer, Jean-Pierre

2013-01-01

The aim of this study was to assess mental workload in which various load sources must be integrated to derive reliable workload estimates. We report a new algorithm for computing weights from qualitative fuzzy integrals and apply it to the National Aeronautics and Space Administration -Task Load indeX (NASA-TLX) subscales in order to replace the standard pair-wise weighting technique (PWT). In this paper, two empirical studies were reported: (1) In a laboratory experiment, age- and task-related variables were investigated in 53 male volunteers and (2) In a field study, task- and job-related variables were studied on aircrews during 48 commercial flights. The results found in this study were as follows: (i) in the experimental setting, fuzzy estimates were highly correlated with classical (using PWT) estimates; (ii) in real work conditions, replacing PWT by automated fuzzy treatments simplified the NASA-TLX completion; (iii) the algorithm for computing fuzzy estimates provides a new classification procedure sensitive to various variables of work environments and (iv) subjective and objective measures can be used for the fuzzy aggregation of NASA-TLX subscales. NASA-TLX, a classical tool for mental workload assessment, is based on a weighted sum of ratings from six subscales. A new algorithm, which impacts on input data collection and computes weights and indexes from qualitative fuzzy integrals, is evaluated through laboratory and field studies. Pros and cons are discussed.

NASA Tech Briefs, November 2007

NASA Technical Reports Server (NTRS)

2007-01-01

Topics include: Wireless Measurement of Contact and Motion Between Contact Surfaces; Wireless Measurement of Rotation and Displacement Rate; Portable Microleak-Detection System; Free-to-Roll Testing of Airplane Models in Wind Tunnels; Cryogenic Shrouds for Testing Thermal-Insulation Panels; Optoelectronic System Measures Distances to Multiple Targets; Tachometers Derived From a Brushless DC Motor; Algorithm-Based Fault Tolerance for Numerical Subroutines; Computational Support for Technology- Investment Decisions; DSN Resource Scheduling; Distributed Operations Planning; Phase-Oriented Gear Systems; Freeze Tape Casting of Functionally Graded Porous Ceramics; Electrophoretic Deposition on Porous Non- Conductors; Two Devices for Removing Sludge From Bioreactor Wastewater; Portable Unit for Metabolic Analysis; Flash Diffusivity Technique Applied to Individual Fibers; System for Thermal Imaging of Hot Moving Objects; Large Solar-Rejection Filter; Improved Readout Scheme for SQUID-Based Thermometry; Error Rates and Channel Capacities in Multipulse PPM; Two Mathematical Models of Nonlinear Vibrations; Simpler Adaptive Selection of Golomb Power-of- Two Codes; VCO PLL Frequency Synthesizers for Spacecraft Transponders; Wide Tuning Capability for Spacecraft Transponders; Adaptive Deadband Synchronization for a Spacecraft Formation; Analysis of Performance of Stereoscopic-Vision Software; Estimating the Inertia Matrix of a Spacecraft; Spatial Coverage Planning for Exploration Robots; and Increasing the Life of a Xenon-Ion Spacecraft Thruster.

A Monte Carlo Approach for Adaptive Testing with Content Constraints

ERIC Educational Resources Information Center

Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander

2008-01-01

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…

Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

NASA Astrophysics Data System (ADS)

Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

2011-06-01

With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Certification Considerations for Adaptive Systems

NASA Technical Reports Server (NTRS)

Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

2015-01-01

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Generalized sidelobe canceller beamforming method for ultrasound imaging.

PubMed

Wang, Ping; Li, Na; Luo, Han-Wu; Zhu, Yong-Kun; Cui, Shi-Gang

2017-03-01

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

A Time Series of Sea Surface Nitrate and Nitrate based New Production in the Global Oceans

NASA Astrophysics Data System (ADS)

Goes, J. I.; Fargion, G. S.; Gomes, H. R.; Franz, B. A.

2014-12-01

With support from NASA's MEaSUREs program, we are developing algorithms for two innovative satellite-based Earth Science Data Records (ESDRs), one Sea Surface Nitrate (SSN) and the other, Nitrate based new Production (NnP). Newly developed algorithms will be applied to mature ESDRs of Chlorophyll a and SST available from NASA, to generate maps of SSN and NnP. Our proposed ESDRs offer the potential of greatly improving our understanding of the role of the oceans in global carbon cycling, earth system processes and climate change, especially for regions and seasons which are inaccessible to traditional shipboard studies. They also provide an innovative means for validating and improving coupled ecosystem models that currently rely on global maps of nitrate generated from multi-year data sets. To aid in our algorithm development efforts and to ensure that our ESDRs are truly global in nature, we are currently in the process of assembling a large database of nutrients from oceanographic institutions all over the world. Once our products are developed and our algorithms are fine-tuned, large-scale data production will be undertaken in collaboration with NASA's Ocean Biology Processing Group (OPBG), who will make the data publicly available first as evaluation products and then as mature ESDRs.

An experimental SMI adaptive antenna array simulator for weak interfering signals

NASA Technical Reports Server (NTRS)

Dilsavor, Ronald S.; Gupta, Inder J.

1991-01-01

An experimental sample matrix inversion (SMI) adaptive antenna array for suppressing weak interfering signals is described. The experimental adaptive array uses a modified SMI algorithm to increase the interference suppression. In the modified SMI algorithm, the sample covariance matrix is redefined to reduce the effect of thermal noise on the weights of an adaptive array. This is accomplished by subtracting a fraction of the smallest eigenvalue of the original covariance matrix from its diagonal entries. The test results obtained using the experimental system are compared with theoretical results. The two show a good agreement.

Modified artificial fish school algorithm for free space optical communication with sensor-less adaptive optics system

NASA Astrophysics Data System (ADS)

Cao, Jingtai; Zhao, Xiaohui; Li, Zhaokun; Liu, Wei; Gu, Haijun

2017-11-01

The performance of free space optical (FSO) communication system is limited by atmospheric turbulent extremely. Adaptive optics (AO) is the significant method to overcome the atmosphere disturbance. Especially, for the strong scintillation effect, the sensor-less AO system plays a major role for compensation. In this paper, a modified artificial fish school (MAFS) algorithm is proposed to compensate the aberrations in the sensor-less AO system. Both the static and dynamic aberrations compensations are analyzed and the performance of FSO communication before and after aberrations compensations is compared. In addition, MAFS algorithm is compared with artificial fish school (AFS) algorithm, stochastic parallel gradient descent (SPGD) algorithm and simulated annealing (SA) algorithm. It is shown that the MAFS algorithm has a higher convergence speed than SPGD algorithm and SA algorithm, and reaches the better convergence value than AFS algorithm, SPGD algorithm and SA algorithm. The sensor-less AO system with MAFS algorithm effectively increases the coupling efficiency at the receiving terminal with fewer numbers of iterations. In conclusion, the MAFS algorithm has great significance for sensor-less AO system to compensate atmospheric turbulence in FSO communication system.

Angular-contact ball-bearing internal load estimation algorithm using runtime adaptive relaxation

NASA Astrophysics Data System (ADS)

Medina, H.; Mutu, R.

2017-07-01

An algorithm to estimate internal loads for single-row angular contact ball bearings due to externally applied thrust loads and high-operating speeds is presented. A new runtime adaptive relaxation procedure and blending function is proposed which ensures algorithm stability whilst also reducing the number of iterations needed to reach convergence, leading to an average reduction in computation time in excess of approximately 80%. The model is validated based on a 218 angular contact bearing and shows excellent agreement compared to published results.

A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being.

PubMed

Ravindran, Sindhu; Jambek, Asral Bahari; Muthusamy, Hariharan; Neoh, Siew-Chin

2015-01-01

A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.

General purpose graphic processing unit implementation of adaptive pulse compression algorithms

NASA Astrophysics Data System (ADS)

Cai, Jingxiao; Zhang, Yan

2017-07-01

This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

CFA-aware features for steganalysis of color images

NASA Astrophysics Data System (ADS)

Goljan, Miroslav; Fridrich, Jessica

2015-03-01

Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

Quality Scalability Aware Watermarking for Visual Content.

PubMed

Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Scalable coding-based content adaptation poses serious challenges to traditional watermarking algorithms, which do not consider the scalable coding structure and hence cannot guarantee correct watermark extraction in media consumption chain. In this paper, we propose a novel concept of scalable blind watermarking that ensures more robust watermark extraction at various compression ratios while not effecting the visual quality of host media. The proposed algorithm generates scalable and robust watermarked image code-stream that allows the user to constrain embedding distortion for target content adaptations. The watermarked image code-stream consists of hierarchically nested joint distortion-robustness coding atoms. The code-stream is generated by proposing a new wavelet domain blind watermarking algorithm guided by a quantization based binary tree. The code-stream can be truncated at any distortion-robustness atom to generate the watermarked image with the desired distortion-robustness requirements. A blind extractor is capable of extracting watermark data from the watermarked images. The algorithm is further extended to incorporate a bit-plane discarding-based quantization model used in scalable coding-based content adaptation, e.g., JPEG2000. This improves the robustness against quality scalability of JPEG2000 compression. The simulation results verify the feasibility of the proposed concept, its applications, and its improved robustness against quality scalable content adaptation. Our proposed algorithm also outperforms existing methods showing 35% improvement. In terms of robustness to quality scalable video content adaptation using Motion JPEG2000 and wavelet-based scalable video coding, the proposed method shows major improvement for video watermarking.

Computational mechanics analysis tools for parallel-vector supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Nguyen, D. T.; Baddourah, M. A.; Qin, J.

1993-01-01

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigen-solution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization algorithm and domain decomposition. The source code for many of these algorithms is available from NASA Langley.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Simulation and Flight Test Capability for Testing Prototype Sense and Avoid System Elements

NASA Technical Reports Server (NTRS)

Howell, Charles T.; Stock, Todd M.; Verstynen, Harry A.; Wehner, Paul J.

2012-01-01

NASA Langley Research Center (LaRC) and The MITRE Corporation (MITRE) have developed, and successfully demonstrated, an integrated simulation-to-flight capability for evaluating sense and avoid (SAA) system elements. This integrated capability consists of a MITRE developed fast-time computer simulation for evaluating SAA algorithms, and a NASA LaRC surrogate unmanned aircraft system (UAS) equipped to support hardware and software in-the-loop evaluation of SAA system elements (e.g., algorithms, sensors, architecture, communications, autonomous systems), concepts, and procedures. The fast-time computer simulation subjects algorithms to simulated flight encounters/ conditions and generates a fitness report that records strengths, weaknesses, and overall performance. Reviewed algorithms (and their fitness report) are then transferred to NASA LaRC where additional (joint) airworthiness evaluations are performed on the candidate SAA system-element configurations, concepts, and/or procedures of interest; software and hardware components are integrated into the Surrogate UAS research systems; and flight safety and mission planning activities are completed. Onboard the Surrogate UAS, candidate SAA system element configurations, concepts, and/or procedures are subjected to flight evaluations and in-flight performance is monitored. The Surrogate UAS, which can be controlled remotely via generic Ground Station uplink or automatically via onboard systems, operates with a NASA Safety Pilot/Pilot in Command onboard to permit safe operations in mixed airspace with manned aircraft. An end-to-end demonstration of a typical application of the capability was performed in non-exclusionary airspace in October 2011; additional research, development, flight testing, and evaluation efforts using this integrated capability are planned throughout fiscal year 2012 and 2013.

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will the SWE estimation error statistics be improved using this high-resolution dataset? Third, how will the SWE retrieval accuracy be improved using CETB and the new SWE retrieval techniques?

Experiment on a three-beam adaptive array for EHF frequency-hopped signals using a fast algorithm, phase-D

NASA Astrophysics Data System (ADS)

Yen, J. L.; Kremer, P.; Amin, N.; Fung, J.

1989-05-01

The Department of National Defence (Canada) has been conducting studies into multi-beam adaptive arrays for extremely high frequency (EHF) frequency hopped signals. A three-beam 43 GHz adaptive antenna and a beam control processor is under development. An interactive software package for the operation of the array, capable of applying different control algorithms is being written. A maximum signal to jammer plus noise ratio (SJNR) was found to provide superior performance in preventing degradation of user signals in the presence of nearby jammers. A new fast algorithm using a modified conjugate gradient approach was found to be a very efficient way to implement anti-jamming arrays based on maximum SJNR criterion. The present study was intended to refine and simplify this algorithm and to implement the algorithm on an experimental array for real-time evaluation of anti-jamming performance. A three-beam adaptive array was used. A simulation package was used in the evaluation of multi-beam systems using more than three beams and different user-jammer scenarios. An attempt to further reduce the computation burden through continued analysis of maximum SJNR met with limited success. A method to acquire and track an incoming laser beam is proposed.

Experiment on a three-beam adaptive array for EHF frequency-hopped signals using a fast algorithm, phase E

NASA Astrophysics Data System (ADS)

Yen, J. L.; Kremer, P.; Fung, J.

1990-05-01

The Department of National Defence (Canada) has been conducting studies into multi-beam adaptive arrays for extremely high frequency (EHF) frequency hopped signals. A three-beam 43 GHz adaptive antenna and a beam control processor is under development. An interactive software package for the operation of the array, capable of applying different control algorithms is being written. A maximum signal to jammer plus noise ratio (SJNR) has been found to provide superior performance in preventing degradation of user signals in the presence of nearby jammers. A new fast algorithm using a modified conjugate gradient approach has been found to be a very efficient way to implement anti-jamming arrays based on maximum SJNR criterion. The present study was intended to refine and simplify this algorithm and to implement the algorithm on an experimental array for real-time evaluation of anti-jamming performance. A three-beam adaptive array was used. A simulation package was used in the evaluation of multi-beam systems using more than three beams and different user-jammer scenarios. An attempt to further reduce the computation burden through further analysis of maximum SJNR met with limited success. The investigation of a new angle detector for spatial tracking in heterodyne laser space communications was completed.

Control algorithms for aerobraking in the Martian atmosphere

NASA Technical Reports Server (NTRS)

Ward, Donald T.; Shipley, Buford W., Jr.

1991-01-01

The Analytic Predictor Corrector (APC) and Energy Controller (EC) atmospheric guidance concepts were adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. Changes are made to the APC to improve its robustness to density variations. These changes include adaptation of a new exit phase algorithm, an adaptive transition velocity to initiate the exit phase, refinement of the reference dynamic pressure calculation and two improved density estimation techniques. The modified controller with the hybrid density estimation technique is called the Mars Hybrid Predictor Corrector (MHPC), while the modified controller with a polynomial density estimator is called the Mars Predictor Corrector (MPC). A Lyapunov Steepest Descent Controller (LSDC) is adapted to control the vehicle. The LSDC lacked robustness, so a Lyapunov tracking exit phase algorithm is developed to guide the vehicle along a reference trajectory. This algorithm, when using the hybrid density estimation technique to define the reference path, is called the Lyapunov Hybrid Tracking Controller (LHTC). With the polynomial density estimator used to define the reference trajectory, the algorithm is called the Lyapunov Tracking Controller (LTC). These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. The MHPC, MPC, LHTC, and LTC show dramatic improvements in robustness over the APC and EC.

Interleaved diffusion-weighted EPI improved by adaptive partial-Fourier and multi-band multiplexed sensitivity-encoding reconstruction

PubMed Central

Chang, Hing-Chiu; Guhaniyogi, Shayan; Chen, Nan-kuei

2014-01-01

Purpose We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion weighted imaging (DWI). Methods First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either a) motion-induced k-space energy peak displacement, or b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multi-band MUSE, so that both through-plane and in-plane aliasing artifacts in multi-band multi-shot interleaved DWI data can be effectively eliminated. Results The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multi-band and high-throughput DWI. Conclusion The integration of the multi-band and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses. PMID:24925000

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks using feasibly-implementable rate adaptivity. • A buffer-management algorithm that is designed to reduce the size of router buffers, and hence energy consumed. • A packet-scheduling algorithm designed to minimize packet-processing energy requirements. Additional research is recommended in at least two areas: further exploration of rate-adaptation in network switching equipment, including incorporation of rate-adaptation in actual hardware, allowing experimentation in operational networks; and development of control protocols that allow parts of networks to be shut down while minimizing disruption to traffic flow in the network. The research is an integral part of a large effort within Bell Laboratories, Alcatel-Lucent, aimed at dramatic improvements in the energy efficiency of telecommunication networks. This Study did not explicitly consider any commercialization opportunities.« less

Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach.

PubMed

Elaziz, Mohamed Abd; Hemdan, Ahmed Monem; Hassanien, AboulElla; Oliva, Diego; Xiong, Shengwu

2017-09-07

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

Wavelet methods in multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Helin, T.; Yudytskiy, M.

2013-08-01

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2017-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2016-12-01

To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2016-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered-reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1984-01-01

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Robust Adaptive Thresholder For Document Scanning Applications

NASA Astrophysics Data System (ADS)

Hsing, To R.

1982-12-01

In document scanning applications, thresholding is used to obtain binary data from a scanner. However, due to: (1) a wide range of different color backgrounds; (2) density variations of printed text information; and (3) the shading effect caused by the optical systems, the use of adaptive thresholding to enhance the useful information is highly desired. This paper describes a new robust adaptive thresholder for obtaining valid binary images. It is basically a memory type algorithm which can dynamically update the black and white reference level to optimize a local adaptive threshold function. The results of high image quality from different types of simulate test patterns can be obtained by this algorithm. The software algorithm is described and experiment results are present to describe the procedures. Results also show that the techniques described here can be used for real-time signal processing in the varied applications.

Processing of fetal heart rate through non-invasive adaptive system based on recursive least squares algorithm

NASA Astrophysics Data System (ADS)

Fajkus, Marcel; Nedoma, Jan; Martinek, Radek; Vasinek, Vladimir

2017-10-01

In this article, we describe an innovative non-invasive method of Fetal Phonocardiography (fPCG) using fiber-optic sensors and adaptive algorithm for the measurement of fetal heart rate (fHR). Conventional PCG is based on a noninvasive scanning of acoustic signals by means of a microphone placed on the thorax. As for fPCG, the microphone is placed on the maternal abdomen. Our solution is based on patent pending non-invasive scanning of acoustic signals by means of a fiber-optic interferometer. Fiber-optic sensors are resistant to technical artifacts such as electromagnetic interferences (EMI), thus they can be used in situations where it is impossible to use conventional EFM methods, e.g. during Magnetic Resonance Imaging (MRI) examination or in case of delivery in water. The adaptive evaluation system is based on Recursive least squares (RLS) algorithm. Based on real measurements provided on five volunteers with their written consent, we created a simplified dynamic signal model of a distribution of heartbeat sounds (HS) through the human body. Our created model allows us to verification of the proposed adaptive system RLS algorithm. The functionality of the proposed non-invasive adaptive system was verified by objective parameters such as Sensitivity (S+) and Signal to Noise Ratio (SNR).

Robust fundamental frequency estimation in sustained vowels: Detailed algorithmic comparisons and information fusion with adaptive Kalman filtering

PubMed Central

Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.

2014-01-01

There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269

Adaptive Cross-correlation Algorithm and Experiment of Extended Scene Shack-Hartmann Wavefront Sensing

NASA Technical Reports Server (NTRS)

Sidick, Erkin; Morgan, Rhonda M.; Green, Joseph J.; Ohara, Catherine M.; Redding, David C.

2007-01-01

We have developed a new, adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels in two extended-scene images captured by a Shack-Hartmann wavefront sensor (SH-WFS). It determines the positions of all of the extended-scene image cells relative to a reference cell using an FFT-based iterative image shifting algorithm. It works with both point-source spot images as well as extended scene images. We have also set up a testbed for extended0scene SH-WFS, and tested the ACC algorithm with the measured data of both point-source and extended-scene images. In this paper we describe our algorithm and present out experimental results.

Selection method of terrain matching area for TERCOM algorithm

NASA Astrophysics Data System (ADS)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Single-pass incremental force updates for adaptively restrained molecular dynamics.

PubMed

Singh, Krishna Kant; Redon, Stephane

2018-03-30

Adaptively restrained molecular dynamics (ARMD) allows users to perform more integration steps in wall-clock time by switching on and off positional degrees of freedoms. This article presents new, single-pass incremental force updates algorithms to efficiently simulate a system using ARMD. We assessed different algorithms for speedup measurements and implemented them in the LAMMPS MD package. We validated the single-pass incremental force update algorithm on four different benchmarks using diverse pair potentials. The proposed algorithm allows us to perform simulation of a system faster than traditional MD in both NVE and NVT ensembles. Moreover, ARMD using the new single-pass algorithm speeds up the convergence of observables in wall-clock time. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants

NASA Astrophysics Data System (ADS)

Masri Husam Fayiz, Al

2017-01-01

The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms.

Blind deconvolution post-processing of images corrected by adaptive optics

NASA Astrophysics Data System (ADS)

Christou, Julian C.

1995-08-01

Experience with the adaptive optics system at the Starfire Optical Range has shown that the point spread function is non-uniform and varies both spatially and temporally as well as being object dependent. Because of this, the application of a standard linear and non-linear deconvolution algorithms make it difficult to deconvolve out the point spread function. In this paper we demonstrate the application of a blind deconvolution algorithm to adaptive optics compensated data where a separate point spread function is not needed.

Lossless Video Sequence Compression Using Adaptive Prediction

NASA Technical Reports Server (NTRS)

Li, Ying; Sayood, Khalid

2007-01-01

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

IMAGESEER - IMAGEs for Education and Research

NASA Technical Reports Server (NTRS)

Le Moigne, Jacqueline; Grubb, Thomas; Milner, Barbara

2012-01-01

IMAGESEER is a new Web portal that brings easy access to NASA image data for non-NASA researchers, educators, and students. The IMAGESEER Web site and database are specifically designed to be utilized by the university community, to enable teaching image processing (IP) techniques on NASA data, as well as to provide reference benchmark data to validate new IP algorithms. Along with the data and a Web user interface front-end, basic knowledge of the application domains, benchmark information, and specific NASA IP challenges (or case studies) are provided.

Filtered-x generalized mixed norm (FXGMN) algorithm for active noise control

NASA Astrophysics Data System (ADS)

Song, Pucha; Zhao, Haiquan

2018-07-01

The standard adaptive filtering algorithm with a single error norm exhibits slow convergence rate and poor noise reduction performance under specific environments. To overcome this drawback, a filtered-x generalized mixed norm (FXGMN) algorithm for active noise control (ANC) system is proposed. The FXGMN algorithm is developed by using a convex mixture of lp and lq norms as the cost function that it can be viewed as a generalized version of the most existing adaptive filtering algorithms, and it will reduce to a specific algorithm by choosing certain parameters. Especially, it can be used to solve the ANC under Gaussian and non-Gaussian noise environments (including impulsive noise with symmetric α -stable (SαS) distribution). To further enhance the algorithm performance, namely convergence speed and noise reduction performance, a convex combination of the FXGMN algorithm (C-FXGMN) is presented. Moreover, the computational complexity of the proposed algorithms is analyzed, and a stability condition for the proposed algorithms is provided. Simulation results show that the proposed FXGMN and C-FXGMN algorithms can achieve better convergence speed and higher noise reduction as compared to other existing algorithms under various noise input conditions, and the C-FXGMN algorithm outperforms the FXGMN.

Development of an Aircraft Approach and Departure Atmospheric Profile Generation Algorithm

NASA Technical Reports Server (NTRS)

Buck, Bill K.; Velotas, Steven G.; Rutishauser, David K. (Technical Monitor)

2004-01-01

In support of NASA Virtual Airspace Modeling and Simulation (VAMS) project, an effort was initiated to develop and test techniques for extracting meteorological data from landing and departing aircraft, and for building altitude based profiles for key meteorological parameters from these data. The generated atmospheric profiles will be used as inputs to NASA s Aircraft Vortex Spacing System (AVOLSS) Prediction Algorithm (APA) for benefits and trade analysis. A Wake Vortex Advisory System (WakeVAS) is being developed to apply weather and wake prediction and sensing technologies with procedures to reduce current wake separation criteria when safe and appropriate to increase airport operational efficiency. The purpose of this report is to document the initial theory and design of the Aircraft Approach Departure Atmospheric Profile Generation Algorithm.

Preliminary Results of NASA's First Autonomous Formation Flying Experiment: Earth Observing-1 (EO-1)

NASA Technical Reports Server (NTRS)

Folta, David; Hawkins, Albin

2001-01-01

NASA's first autonomous formation flying mission is completing a primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Guidance, Navigation, and Control center at the Goddard Space Flight Center has implemented an autonomous universal three-axis formation flying algorithm in executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm and the onboard design and presents the preliminary validation results of this unique system. Results from functionality assessment and autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(tm), its ground-based predecessor, and a stand-alone algorithm.

Memory-Efficient Onboard Rock Segmentation

NASA Technical Reports Server (NTRS)

Burl, Michael C.; Thompson, David R.; Bornstein, Benjamin J.; deGranville, Charles K.

2013-01-01

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Development of Variable Camber Continuous Trailing Edge Flap for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Kaul, Upender; Lebofsky, Sonia; Ting, Eric; Chaparro, Daniel; Urnes, James

2015-01-01

This paper summarizes the recent development of an adaptive aeroelastic wing shaping control technology called variable camber continuous trailing edge flap (VCCTEF). As wing flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. The initial VCCTEF concept was developed in 2010 by NASA under a NASA Innovation Fund study entitled "Elastically Shaped Future Air Vehicle Concept," which showed that highly flexible wing aerodynamic surfaces can be elastically shaped in-flight by active control of wing twist and bending deflection in order to optimize the spanwise lift distribution for drag reduction. A collaboration between NASA and Boeing Research & Technology was subsequently funded by NASA from 2012 to 2014 to further develop the VCCTEF concept. This paper summarizes some of the key research areas conducted by NASA during the collaboration with Boeing Research and Technology. These research areas include VCCTEF design concepts, aerodynamic analysis of VCCTEF camber shapes, aerodynamic optimization of lift distribution for drag minimization, wind tunnel test results for cruise and high-lift configurations, flutter analysis and suppression control of flexible wing aircraft, and multi-objective flight control for adaptive aeroelastic wing shaping control.

Parallel processors and nonlinear structural dynamics algorithms and software

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Gilbertsen, Noreen D.; Neal, Mark O.; Plaskacz, Edward J.

1989-01-01

The adaptation of a finite element program with explicit time integration to a massively parallel SIMD (single instruction multiple data) computer, the CONNECTION Machine is described. The adaptation required the development of a new algorithm, called the exchange algorithm, in which all nodal variables are allocated to the element with an exchange of nodal forces at each time step. The architectural and C* programming language features of the CONNECTION Machine are also summarized. Various alternate data structures and associated algorithms for nonlinear finite element analysis are discussed and compared. Results are presented which demonstrate that the CONNECTION Machine is capable of outperforming the CRAY XMP/14.

Glint-induced false alarm reduction in signature adaptive target detection

NASA Astrophysics Data System (ADS)

Crosby, Frank J.

2002-07-01

The signal adaptive target detection algorithm developed by Crosby and Riley uses target geometry to discern anomalies in local backgrounds. Detection is not restricted based on specific target signatures. The robustness of the algorithm is limited by an increased false alarm potential. The base algorithm is extended to eliminate one common source of false alarms in a littoral environment. This common source is glint reflected on the surface of water. The spectral and spatial transience of glint prevent straightforward characterization and complicate exclusion. However, the statistical basis of the detection algorithm and its inherent computations allow for glint discernment and the removal of its influence.

Multiple Autonomous Discrete Event Controllers for Constellations

NASA Technical Reports Server (NTRS)

Esposito, Timothy C.

2003-01-01

The Multiple Autonomous Discrete Event Controllers for Constellations (MADECC) project is an effort within the National Aeronautics and Space Administration Goddard Space Flight Center's (NASA/GSFC) Information Systems Division to develop autonomous positioning and attitude control for constellation satellites. It will be accomplished using traditional control theory and advanced coordination algorithms developed by the Johns Hopkins University Applied Physics Laboratory (JHU/APL). This capability will be demonstrated in the discrete event control test-bed located at JHU/APL. This project will be modeled for the Leonardo constellation mission, but is intended to be adaptable to any constellation mission. To develop a common software architecture. the controllers will only model very high-level responses. For instance, after determining that a maneuver must be made. the MADECC system will output B (Delta)V (velocity change) value. Lower level systems must then decide which thrusters to fire and for how long to achieve that (Delta)V.

Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder

NASA Technical Reports Server (NTRS)

Lindsey, A. E.; Pecheur, Charles

2004-01-01

AI software is often used as a means for providing greater autonomy to automated systems, capable of coping with harsh and unpredictable environments. Due in part to the enormous space of possible situations that they aim to addrs, autonomous systems pose a serious challenge to traditional test-based verification approaches. Efficient verification approaches need to be perfected before these systems can reliably control critical applications. This publication describes Livingstone PathFinder (LPF), a verification tool for autonomous control software. LPF applies state space exploration algorithms to an instrumented testbed, consisting of the controller embedded in a simulated operating environment. Although LPF has focused on NASA s Livingstone model-based diagnosis system applications, the architecture is modular and adaptable to other systems. This article presents different facets of LPF and experimental results from applying the software to a Livingstone model of the main propulsion feed subsystem for a prototype space vehicle.

Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis.

PubMed

Wei, Qinglai; Liu, Derong; Lin, Qiao

In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Gradient maintenance: A new algorithm for fast online replanning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahunbay, Ergun E., E-mail: eahunbay@mcw.edu; Li, X. Allen

2015-06-15

Purpose: Clinical use of online adaptive replanning has been hampered by the unpractically long time required to delineate volumes based on the image of the day. The authors propose a new replanning algorithm, named gradient maintenance (GM), which does not require the delineation of organs at risk (OARs), and can enhance automation, drastically reducing planning time and improving consistency and throughput of online replanning. Methods: The proposed GM algorithm is based on the hypothesis that if the dose gradient toward each OAR in daily anatomy can be maintained the same as that in the original plan, the intended plan qualitymore » of the original plan would be preserved in the adaptive plan. The algorithm requires a series of partial concentric rings (PCRs) to be automatically generated around the target toward each OAR on the planning and the daily images. The PCRs are used in the daily optimization objective function. The PCR dose constraints are generated with dose–volume data extracted from the original plan. To demonstrate this idea, GM plans generated using daily images acquired using an in-room CT were compared to regular optimization and image guided radiation therapy repositioning plans for representative prostate and pancreatic cancer cases. Results: The adaptive replanning using the GM algorithm, requiring only the target contour from the CT of the day, can be completed within 5 min without using high-power hardware. The obtained adaptive plans were almost as good as the regular optimization plans and were better than the repositioning plans for the cases studied. Conclusions: The newly proposed GM replanning algorithm, requiring only target delineation, not full delineation of OARs, substantially increased planning speed for online adaptive replanning. The preliminary results indicate that the GM algorithm may be a solution to improve the ability for automation and may be especially suitable for sites with small-to-medium size targets surrounded by several critical structures.« less

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Evaluation of Algorithms for Compressing Hyperspectral Data

NASA Technical Reports Server (NTRS)

Cook, Sid; Harsanyi, Joseph; Faber, Vance

2003-01-01

With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

ASTAR Flight Test: Overview and Spacing Results

NASA Technical Reports Server (NTRS)

Roper, Roy D.; Koch, Michael R.

2016-01-01

The purpose of the NASA Langley Airborne Spacing for Terminal Arrival Routes (ASTAR) research aboard the Boeing ecoDemonstrator aircraft was to demonstrate the use of NASA's ASTAR algorithm using contemporary tools of the Federal Aviation Administration's Next Generation Air Transportation System (NEXTGEN). EcoDemonstrator is a Boeing test program which utilizes advanced experimental equipment to accelerate the science of aerospace and environmentally friendly technologies. The ASTAR Flight Test provided a proof-of-concept flight demonstration that exercised an algorithmic-based application in an actual aircraft. The test aircraft conducted Interval Management operations to provide time-based spacing off a target aircraft in non-simulator wind conditions. Work was conducted as a joint effort between NASA and Boeing to integrate ASTAR in a Boeing supplied B787 test aircraft while using a T-38 aircraft as the target. This demonstration was also used to identify operational risks to future flight trials for the NASA Air Traffic Management Technology Demonstration expected in 2017.

Orion Stage Adapter move to Redstone Airfield

NASA Image and Video Library

2018-04-03

NASA's Super Guppy aircraft arrives to the U.S. Army’s Redstone Airfield in Huntsville, Alabama, April 2, to pick up flight hardware for NASA’s Space Launch System – its new, deep-space rocket that will enable astronauts to begin their journey to explore destinations far into the solar system. The Guppy will depart on Tuesday, April 3 to deliver the Orion stage adapter to NASA’s Kennedy Space Center in Florida for flight preparations. On Exploration Mission-1, the first integrated flight of the SLS and the Orion spacecraft, the adapter will connect Orion to the rocket and carry 13 CubeSats as secondary payloads. Rumaasha Maasha, an aerospace engineer in Marshall's Spacecraft & Vehicle Systems Department, tours the cockpit of NASA's Super Guppy aircraft April 3 when it landed at Marshall to pick up the Orion stage adapter for transportation to NASA's Kennedy Space Center. Maasha holds a master's degree in aerospace engineering, is a certified aviation maintenance tech and pilot and previously worked as a 747 loadmaster and airline refueler.

Genetic algorithms

NASA Technical Reports Server (NTRS)

Wang, Lui; Bayer, Steven E.

1991-01-01

Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

Retrieving Atmospheric Profiles Data in the Presence of Clouds from Hyperspectral Remote Sensing Data

NASA Technical Reports Server (NTRS)

Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.;

An implicit adaptation algorithm for a linear model reference control system

NASA Technical Reports Server (NTRS)

Mabius, L.; Kaufman, H.

1975-01-01

This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.