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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

Callosally projecting neurons in the macaque monkey V1/V2 border are enriched in nonphosphorylated neurofilament protein

Previous immunohistochemical studies combined with retrograde tracing in macaque monkeys have demonstrated that corticocortical projections can be differentiated by their content of neurofilament protein. The present study analyzed the distribution of nonphosphorylated neurofilament protein in callosally projecting neurons located at the V1/V2 border. All of the retrogradely labeled neurons were located in layer III at the V1/V2 border and at an immediately adjacent zone of area V2. A quantitative analysis showed that the vast majority (almost 95%) of these interhemispheric projection neurons contain neurofilament protein immunoreactivity. This observation differs from data obtained in other sets of callosal connections, including homotypical interhemispheric projections in the prefrontal, temporal, and parietal association cortices, that were found to contain uniformly low proportions of neurofilament protein-immunoreactive neurons. Comparably, highly variable proportions of neurofilament protein-containing neurons have been reported in intrahemispheric corticocortical pathways, including feedforward and feedback visual connections. These results indicate that neurofilament protein is a prominent neurochemical feature that identifies a particular population of interhemispheric projection neurons at the V1/V2 border and suggest that this biochemical attribute may be critical for the function of this subset of callosal neurons.

Non-NASA Center↗

Morphological evidence for local microcircuits in rat vestibular maculae

Previous studies suggested that intramacular, unmyelinated segments of vestibular afferent nerve fibers and their large afferent endings (calyces) on type I hair cells branch. Many of the branches (processes) contain vesicles and are presynaptic to type II hair cells, other processes, intramacular nerve fibers, and calyces. This study used serial section transmission electron microscopy and three-dimensional reconstruction methods to document the origins and distributions of presynaptic processes of afferents in the medial part of the adult rat utricular macula. The ultrastructural research focused on presynaptic processes whose origin and termination could be observed in a single micrograph. Results showed that calyces had 1) vesiculated, spine-like processes that invaginated type I cells and 2) other, elongate processes that ended on type II cells pre- as well as postsynaptically. Intramacular, unmyelinated segments of afferent nerve fibers gave origin to branches that were presynaptic to type II cells, calyces, calyceal processes, and other nerve fibers in the macula. Synapses with type II cells occurred opposite subsynaptic cisternae (C synapses); all other synapses were asymmetric. Vesicles were pleomorphic but were differentially distributed according to process origin. Small, clear-centered vesicles, approximately 40-60 nm in diameter, predominated in processes originating from afferent nerve fibers and basal parts of calyces. Larger vesicles approximately 70-120 nm in diameter having approximately 40-80 nm electron-opaque cores were dominant in processes originating from the necks of calyces. Results are interpreted to indicate the existence of a complex system of intrinsic feedforward (postsynaptic)-feedback (presynaptic) connections in a network of direct and local microcircuits. The morphological findings support the concept that maculae dynamically preprocess linear acceleratory information before its transmission to the central nervous system.

NASA Center ARC↗

Linear and nonlinear ARMA model parameter estimation using an artificial neural network

This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.

NASA Discipline Regulatory Physiology↗

Intelligent, Robust Control of Deteriorated Turbofan Engines via Linear Parameter Varying Quadratic Lyapunov Function Design

A method for accommodating engine deterioration via a scheduled Linear Parameter Varying Quadratic Lyapunov Function (LPVQLF)-Based controller is presented. The LPVQLF design methodology provides a means for developing unconditionally stable, robust control of Linear Parameter Varying (LPV) systems. The controller is scheduled on the Engine Deterioration Index, a function of estimated parameters that relate to engine health, and is computed using a multilayer feedforward neural network. Acceptable thrust response and tight control of exhaust gas temperature (EGT) is accomplished by adjusting the performance weights on these parameters for different levels of engine degradation. Nonlinear simulations demonstrate that the controller achieves specified performance objectives while being robust to engine deterioration as well as engine-to-engine variations.

Turso, James A.↗

An optimal controller for an electric ventricular-assist device: theory, implementation, and testing

This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.

Therapy, Computer-Assisted/standards↗

Model-Trained Neural Networks and Electronic Holography Demonstrated to Detect Damage in Blades

Detect Damage in Blades Electronic holography can show damaged regions in fan blades at 30 frames/sec. The electronic holograms are transformed by finite-element-model-trained artificial neural networks to visualize the damage. The trained neural networks are linked with video and graphics to visualize the bending-induced strain distribution, which is very sensitive to damage. By contrast, it is very difficult to detect damage by viewing the raw, speckled, characteristic fringe patterns. For neural-network visualization of damage, 2 frames or 2 fields are used, rather than the 12 frames normally used to compute the displacement distribution from electronic holograms. At the NASA Lewis Research Center, finite element models are used to compute displacement and strain distributions for the vibration modes of undamaged and cracked blades. A model of electronic time-averaged holography is used to transform the displacement distributions into finite-element-resolution characteristic fringe patterns. Then, a feedforward neural network is trained with the fringe-pattern/strain-pattern pairs, and the neural network, electronic holography, and video are implemented on a workstation. Now that the neural networks have been tested successfully at 30 frames/sec on undamaged and cracked cantilevers, the electronic holography and neural-network processing are being adapted for onsite damage inspection of twisted fan blades and rotormounted blades. Our conclusion is that model-trained neural nets are effective when they are trained with good models whose application is well understood. This work supports the aeromechanical testing portion of the Advanced Subsonic Technology Project.

Decker, Arthur J.↗

Exploratory Studies in Generalized Predictive Control for Active Gust Load Alleviation

The results of numerical simulations aimed at assessing the efficacy of Generalized Predictive Control (GPC) for active gust load alleviation using trailing- and leading-edge control surfaces are presented. The equations underlying the method are presented and discussed, including system identification, calculation of control law matrices, and calculation of commands applied to the control effectors. Both embedded and explicit feedforward paths for inclusion of disturbance effects are addressed. Results from two types of simulations are shown. The first used a 3-DOF math model of a mass-spring-dashpot system subject to user-defined external disturbances. The second used open-loop data from a wind-tunnel test in which a wing model was excited by sinusoidal vertical gusts; closed-loop behavior was simulated in post-test calculations. Results obtained from these simulations have been decidedly positive. In particular, results of closed-loop simulations for the wing model showed reductions in root moments by factors as high as 1000, depending on whether the excitation is from a constant- or variable-frequency gust and on the direction of the response.

Kvaternik, Raymond G.↗

High Fidelity System Simulation of Multiple Components in Support of the UEET Program

The High Fidelity System Simulation effort has addressed various important objectives to enable additional capability within the NPSS framework. The scope emphasized High Pressure Turbine and High Pressure Compressor components. Initial effort was directed at developing and validating intermediate fidelity NPSS model using PD geometry and extended to high-fidelity NPSS model by overlaying detailed geometry to validate CFD against rig data. Both "feedforward" and feedback" approaches of analysis zooming was employed to enable system simulation capability in NPSS. These approaches have certain benefits and applicability in terms of specific applications "feedback" zooming allows the flow-up of information from high-fidelity analysis to be used to update the NPSS model results by forcing the NPSS solver to converge to high-fidelity analysis predictions. This apporach is effective in improving the accuracy of the NPSS model; however, it can only be used in circumstances where there is a clear physics-based strategy to flow up the high-fidelity analysis results to update the NPSS system model. "Feed-forward" zooming approach is more broadly useful in terms of enabling detailed analysis at early stages of design for a specified set of critical operating points and using these analysis results to drive design decisions early in the development process.

Plybon, Ronald C.↗

GOES-R STATIONKEEPING AND MOMENTUM MANAGEMENT

The NOAA Geostationary Operational Environmental Satellites (GOES) fire thrusters to remain within a 1deg longitude-latitude box and to dump accumulated angular momentum. In the past, maneuvers have disrupted GOES imaging due to attitude transients and the loss of orbit knowledge. If the R-series of spacecraft to be launched starting in 2012 were to follow current practice, maneuvers would still fail to meet Image Navigation and Registration (INR) specifications during and after thruster firings. Although maneuvers and recovery take only one percent of spacecraft lifetime, they sometimes come at inopportune times, such as hurricane season, when coverage is critical. To alleviate this problem, thruster firings small enough not to affect imaging are being considered. Eliminating post-maneuver recovery periods increases availability and facilitates autonomous operation. Frequent maneuvers also reduce 1ongitudeAatitude variation and allow satellite co-location. Improved orbit observations come from a high-altitude GPS receiver, and improved attitude control comes from thruster torque compensation. This paper reviews the effects of thruster firings on position knowledge and pointing control and suggests that low-thrust burns plus GPS and feedforward control offer a less disruptive approach to GOES-R stationkeeping and momentum management.

Chu, Donald↗

Development of an Experimental Rig for Investigation of Higher Order Modes in Ducts

Continued progress to reduce fan noise emission from high bypass ratio engine ducts in aircraft increasingly relies on accurate description of the sound propagation in the duct. A project has been undertaken at NASA Langley Research Center to investigate the propagation of higher order modes in ducts with flow. This is a two-pronged approach, including development of analytic models (the subject of a separate paper) and installation of a laboratory-quality test rig. The purposes of the rig are to validate the analytical models and to evaluate novel duct acoustic liner concepts, both passive and active. The dimensions of the experimental rig test section scale to between 25% and 50% of the aft bypass ducts of most modern engines. The duct is of rectangular cross section so as to provide flexibility to design and fabricate test duct liner samples. The test section can accommodate flow paths that are straight through or offset from inlet to discharge, the latter design allowing investigation of the effect of curvature on sound propagation and duct liner performance. The maximum air flow rate through the duct is Mach 0.3. Sound in the duct is generated by an array of 16 high-intensity acoustic drivers. The signals to the loudspeaker array are generated by a multi-input/multi-output feedforward control system that has been developed for this project. The sound is sampled by arrays of flush-mounted microphones and a modal decomposition is performed at the frequency of sound generation. The data acquisition system consists of two arrays of flush-mounted microphones, one upstream of the test section and one downstream. The data are used to determine parameters such as the overall insertion loss of the test section treatment as well as the effect of the treatment on a modal basis such as mode scattering. The methodology used for modal decomposition is described, as is a description of the mode generation control system. Data are presented which demonstrate the performance of the controller to generate the desired mode while suppressing all other cut on modes in the duct.

Gerhold, Carl H.↗

Control of a simulated arm using a novel combination of Cerebellar learning mechanisms

We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.

cerebellum cerebellar learning dynamic state estim↗

Entry Attitude Controller for the Mars Science Laboratory

This paper describes the preliminary concept for the RCS 3-axis attitude controller for the exo-atmospheric and guided entry phases of the Mars Science Laboratory Entry, Descend and Landing. The entry controller is formulated as three independent channels in the control frame, which is nominally aligned with the stability frame. Each channel has a feedfoward and a feedback. The feedforward path enables fast response to large bank commands. The feedback path stabilizes the vehicle angle of attack and sideslip around its trim position, and tracks bank commands. The feedback path has a PD/D structure with deadbands that minimizes fuel usage. The performance of this design is demonstrated via simulation.

Mars↗

Dual-arm manipulators with adaptive control

The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

Seraji, Homayoun↗

Method and apparatus for adaptive force and position control of manipulators

The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

Seraji, Homayoun↗

Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.

model predictive control algorithm (MPC)↗

Handling Qualities Evaluation of Pilot Tools for Spacecraft Docking in Earth Orbit

A new generation of spacecraft is now under development by NASA to replace the Space Shuttle and return astronauts to the Moon. These spacecraft will have a manual control capability for several mission tasks, and the ease and precision with which pilots can execute these tasks will have an important effect on mission risk and training costs. This paper focuses on the handling qualities of a spacecraft based on dynamics similar to that of the Crew Exploration Vehicle, during the last segment of the docking task with a space station in low Earth orbit. A previous study established that handling qualities for this task degrade significantly as the level of translation-into-rotation coupling increases. The goal of this study is to evaluate the efficacy of various pilot aids designed to mitigate the handling qualities degradation caused by this coupling. Four pilot tools were ev adluaetead:d-band box/indicator, flight-path marker, translation guidance cues, and feed-forward control. Each of these pilot tools improved handling qualities, generally with greater improvements resulting from using these tools in combination. A key result of this study is that feedforward control effectively counteracts coupling effects, providing solid Level 1 handling qualities for the spacecraft configuration evaluated.

Bilimoria, Karl D.↗

Instrument Pointing Control System for the Stellar Interferometry Mission - Planet Quest

This paper describes the high precision Instrument Pointing Control System (PCS) for the Stellar Interferometry Mission (SIM) - Planet Quest. The PCS system provides front-end pointing, compensation for spacecraft motion, and feedforward stabilization, which are needed for proper interference. Optical interferometric measurements require very precise pointing (0.03 as, 1-(sigma) radial) for maximizing the interference pattern visibility. This requirement is achieved by fine pointing control of articulating pointing mirrors with feedback from angle tracking cameras. The overall pointing system design concept is presentcd. Functional requirements and an acquisition concept are given. Guide and Science pointing control loops are discussed. Simulation analyses demonstrate the feasibility of the design.

control↗

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗