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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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A new GAL4-based feed-forward loop circuit enhances β-glucuronidase (GUS) reporter gene expression in leaves and stems of stably transformed sugarcane plants.
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This paper will describe the STB3 setup, the pathlength control architecture and the data collected with the system and how they relate to SIM.
Connectionist feed-forward networks, trained with back-propagation, can be used both for nonlinear regression and for (discrete one-of-C) classification, depending on the form of training. This report contains two papers on feed-forward networks. The papers can be read independently. They are intended for the theoretically-aware practitioner or algorithm-designer; however, they also contain a review and comparison of several learning theories so they provide a perspective for the theoretician. The first paper works through Bayesian methods to complement back-propagation in the training of feed-forward networks. The second paper addresses a problem raised by the first: how to efficiently calculate second derivatives on feed-forward networks.
This paper describes the design and evaluation of a stochastic optimal feed-forward and feedback technology (SOFFT) control architecture with emphasis on the feed-forward controller design. The SOFFT approach allows the designer to independently design the feed-forward and feedback controllers to meet separate objectives and then integrate the two controllers. The feed-forward controller has been integrated with an existing high-angle-of-attack (high-alpha) feedback controller. The feed-forward controller includes a variable command model with parameters selected to satisfy level 1 flying qualities with a high-alpha adjustment to achieve desired agility guidelines, a nonlinear interpolation approach that scales entire matrices for approximation of the plant model, and equations for calculating feed-forward gains developed for perfect plant-model tracking. The SOFFT design was applied to a nonlinear batch simulation model of an F/A-18 aircraft modified for thrust vectoring. Simulation results show that agility guidelines are met and that the SOFFT controller filters undesired pilot-induced frequencies more effectively during a tracking task than a flight controller that has the same feedback control law but does not have the SOFFT feed-forward control.
A matrix converter system having a current control mode operation is provided. The system includes a matrix converter having a switching matrix. The matrix converter is coupled at its low-voltage side to a generator and at its output load side to a load. A controller having a pulse width modulation (PWM) control circuit is configured to control the matrix converter via its switching matrix to increase energy within the internal inductances of the generator when the switching matrix causes a short circuit. A feed forward calculator is configured to calculate a feed forward output phase angle. The feed forward output phase angle is an estimation of an angle between an output current vector and an output voltage vector that represent feedback signals of current and voltage output by the matrix converter. The angular position of the voltage output vector is adjusted as a function of the feed forward output phase angle to align angular position or phase angle of the voltage output vector that represents the voltage output with a selected angular position or phase angle.
In order to improve the accuracy of high-rate tracking of NASA's DSN antennas, the position-loop controller has been upgraded with a feed-forward loop. Conditions for perfect and approximate tracking with the feed-forward loop are presented. The feed-forward loop improves tracking performance and preserves wind disturbance rejection properties of the previous closed-loop system.
A generalized feed-forward method for accurate tunable laser absorption spectroscopy includes generating a laser beam. The generated laser beam is directed down a reference path and a test/sample path. One or more parameters are extracted from the reference path. The one or more parameters, extracted from the reference path, are used as feed-forward, to adjust spectral analysis of the test/sample path to detect a composition and/or concentration of an analyte gas within the test/sample path. The extraction of the one or more parameters from the reference path and the spectral analysis of the test/sample path are performed substantially concurrently.
A new automatic flight control system concept suitable for aircraft with highly nonlinear aerodynamic and propulsion characteristics and which must operate over a wide flight envelope was investigated. This exact model follower inverts a complete nonlinear model of the aircraft as part of the feed-forward path. The inversion is accomplished by a Newton-Raphson trim of the model at each digital computer cycle time of 0.05 seconds. The combination of the inverse model and the actual aircraft in the feed-forward path alloys the translational and rotational regulators in the feedback path to be easily designed by linear methods. An explanation of the model inversion procedure is presented. An extensive set of simulation data for essentially the full flight envelope for a vertical attitude takeoff and landing aircraft (VATOL) is presented. These data demonstrate the successful, smooth, and precise control that can be achieved with this concept. The trajectory includes conventional flight from 200 to 900 ft/sec with path accelerations and decelerations, altitude changes of over 6000 ft and 2g and 3g turns. Vertical attitude maneuvering as a tail sitter along all axes is demonstrated. A transition trajectory from 200 ft/sec in conventional flight to stationary hover in the vertical attitude includes satisfactory operation through lift-cure slope reversal as attitude goes from horizontal to vertical at constant altitude. A vertical attitude takeoff from stationary hover to conventional flight is also demonstrated.
We develop new uncertainty propagation methods for feed-forward neural network architectures with leaky ReLU activation functions subject to random perturbations in the input vectors. In particular, we derive analytical expressions for the probability density function (PDF) of the neural network output and its statistical moments as a function of the input uncertainty and the parameters of the network, i.e., weights and biases. A key finding is that an appropriate linearization of the leaky ReLU activation function yields accurate statistical results even for large perturbations in the input vectors. This can be attributed to the way information propagates through the network. We also propose new analytically tractable Gaussian copula surrogate models to approximate the full joint PDF of the neural network output. To validate our theoretical results, we conduct Monte Carlo simulations and a thorough error analysis on a multi-layer neural network representing a nonlinear integro-differential operator between two polynomial function spaces. Our findings demonstrate excellent agreement between the theoretical predictions and Monte Carlo simulations.
This paper describes the STB3 setup, the pathlength feed-forward architecture, implementation issues and data collected with the system.
In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.
The novel tri-port current-source medium-voltage string inverter (TCS-MVSI) is a promising candidate for large-scale PV-plus-storage (PVS) farms owing to its galvanic isolation, easy storage integration, soft-switching capability across entire load range, controlled low dv/dt and EMI, benign fault tolerance, etc. Due to its low inertia feature, traditional PI-based control cannot manage large transients effectively. Instead, a model-based predictive control (MPC) is proposed to achieve robust and stable operation. As is well known, the control performance of MPC is compromised by the sampling and computational delay during implementation significantly, if not well addressed. This paper analyzed and quantified these delays and then proposes feed-forward compensation (FFC) for the MPC method to compensate the delays and the large parameter variations due to the low-inertia nature. In addition, this method also compensates for the high dc-link ripple within each switching cycle, a unique issue for low-inertia converters. Here, the proposed method requires low computational effort, allowing it to be extended for multiple ports. The effectiveness of the proposed method has been validated in experiments. In 10 kW test, the proposed method decreases the average dc-link current by 17%, leading to ~20% conduction losses and ~0.5% increase in converter efficiency. In addition, the peak dc-link current also decreases by 15%, resulting in reduced transformer size. As a result, an increased power density can be achieved with the proposed method. Similar improvements have been observed across the power range from 2 kW to 10 kW.
This paper presents a novel means for suppressing gear mesh-related vibrations. The key components in this approach are piezoelectric actuators and a high-frequency, analog feed-forward controller. Test results are presented and show up to a 70-percent reduction in gear mesh acceleration and vibration control up to 4500 Hz. The principle of the approach is explained by an analysis of a harmonically excited, general linear vibratory system.
A full-flight-envelope automatic trajectory control system concept is being investigated at Ames Research Center. This concept was developed for advanced aircraft configurations with severe nonlinear characteristics. A feature of the system is an inverse of the complete nonlinear aircraft model as part of the feed-forward control path. Simulation and flight tests have been reported at previous Digital Avionics Systems conferences. A new method for the continuous real-time inversion of the aircraft model using a Newton-Raphson trim algorithm instead of the original inverse table look-up procedure has been developed. The results of a simulation study of a vertical attitude takeoff and landing aircraft using the new inversion technique are presented. Maneuvers were successfully carried out in all directions in the vertical-attitude hover mode. Transition runs from conventional flight through the region of lift-curve-slope reversal at an angle of attack of about 32 deg and to hover at zero speed in the vertical attitude showed satisfactory transient response. Simulations were also conducted in conventional flight at high subsonic speed in steep climb and with turns up to 4 g. Successful flight tests of the system with the new model-inversion technique in a UH-1H helicopter have recently been carried out.
Technology required to land large payloads (20 to 50 mt) on Mars remains elusive. In an effort to identify the most viable investment path, NASA and others have been studying various concepts. One such study, the Entry, Descent and Landing Systems Analysis (EDLSA) Study [1] identified three potential options: the rigid aeroshell, the inflatable aeroshell and supersonic retropropulsion (SRP). In an effort to drive out additional levels of design detail, a smaller demonstrator, or exploration feed-forward (EFF), robotic mission was devised that utilized two of the three (inflatable aeroshell and SRP) high potential technologies in a configuration to demonstrate landing a two to four metric ton payload on Mars. This paper presents and overview of the maximum landed mass, inflatable aeroshell controllability and sensor suite capability assessments of the selected technologies and recommends specific technology areas for additional work.
NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to successfully land large payloads at Mars for both robotic and human-scale missions. Year 1 of the study focused on technologies required for Exploration-class missions to land payloads of 10 to 50 t. Inflatable decelerators, rigid aeroshell and supersonic retro-propulsion emerged as the top candidate technologies. In Year 2 of the study, low TRL technologies identified in Year 1, inflatables aeroshells and supersonic retropropulsion, were combined to create a demonstration precursor robotic mission. This part of the EDL-SA Year 2 effort, called Exploration Feed Forward (EFF), took much of the systems analysis simulation and component model development from Year 1 to the next level of detail.
NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to successfully land large payloads at Mars for both robotic and human-scale missions. Year 1 of the study focused on technologies required for Exploration-class missions to land payloads of 10 to 50 mt. Inflatable decelerators, rigid aeroshell and supersonic retro-propulsion emerged as the top candidate technologies. In Year 2 of the study, low TRL technologies identified in Year 1, inflatables aeroshells and supersonic retropropulsion, were combined to create a demonstration precursor robotic mission. This part of the EDL-SA Year 2 effort, called Exploration Feed Forward (EFF), took much of the systems analysis simulation and component model development from Year 1 to the next level of detail.