Search NASA⌕ Search

SEARCH · Search NASA

Results for “version control”

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

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

At least 163 records · Page 9

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

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.

adaptive control↗

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

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.

manual steering mode↗

Further developments in exact state reconstruction in deterministic digital control systems

A more general version of the ideal state reconstructor for deterministic digital control systems previously developed is presented. In the original version, measurements prefiltered by a multi-input/multi-output moving-average (MA) process were utilized in the state reconstruction process. In this version, the MA-prefiltered measurements can be supplemented by standard instantaneous measurements. The ideal state reconstructor is so named because: if the plant parameters are known exactly, its output will exactly equal the true state of the plant, not just approximate it. Furthermore, it adds no additional states or eigenvalues to the system. Nor does it affect the plant equation for the system in any way; it affects the measurement equation only. An example is presented which illustrates the procedure for choosing the parameters in it.

Polites, Michael E.↗

Computer simulation of a pilot in V/STOL aircraft control loops

The objective was to develop a computerized adaptive pilot model for the computer model of the research aircraft, the Harrier II AV-8B V/STOL with special emphasis on propulsion control. In fact, two versions of the adaptive pilot are given. The first, simply called the Adaptive Control Model (ACM) of a pilot includes a parameter estimation algorithm for the parameters of the aircraft and an adaption scheme based on the root locus of the poles of the pilot controlled aircraft. The second, called the Optimal Control Model of the pilot (OCM), includes an adaption algorithm and an optimal control algorithm. These computer simulations were developed as a part of the ongoing research program in pilot model simulation supported by NASA Lewis from April 1, 1985 to August 30, 1986 under NASA Grant NAG 3-606 and from September 1, 1986 through November 30, 1988 under NASA Grant NAG 3-729. Once installed, these pilot models permitted the computer simulation of the pilot model to close all of the control loops normally closed by a pilot actually manipulating the control variables. The current version of this has permitted a baseline comparison of various qualitative and quantitative performance indices for propulsion control, the control loops and the work load on the pilot. Actual data for an aircraft flown by a human pilot furnished by NASA was compared to the outputs furnished by the computerized pilot and found to be favorable.

Vogt, William G.↗

Active nutation controller

An apparatus is described for controlling nutation motion in a spinning body, comprised of an angular accelerometer with its input axis perpendicular to the spin axis of the body, a flywheel with an axis of rotation perpendicular to the axis of the accelerometer and to the spin axis of the body, and a motor for driving the flywheel to attenuate or build nutation. The motor is controlled by circuitry that monitors the output of the angular accelerometer and drives the motor clockwise or counterclockwise during predetermined nutation angles synchronized to the zero crossover points of the accelerometer signal centered about the nutation peaks. The motor drive is phased to damp nutation motion to zero for stabilization. To increase the noise immunity of the system, when the output of the accelerometer falls below a threshold level, the circuitry operates in an open loop, beat mode where data representing the last accelerometer signal that exceeded that threshold level is stored, and the motor drive is controlled by the stored data. In a second version, the motor is controlled to supply a predetermined amount of nutation motion to a body undergoing testing on a spin table for energy dissipation evaluation. In each version, the use of an angular accelerometer rather than a linear accelerometer or gyro to monitor nutation enables placement of the nutation control apparatus at any location relative to the spin axis of the body requiring only crude orientation and no calibration.

Hoffman, H. C.↗

NASA Meteoroid Engineering Model (MEM) Version 3

The Meteoroid Engineering Model (MEM) version 3 is NASA’s most current and accurate model of the meteoroid environment. MEM 3 supersedes all previous versions of MEM, including MEM Release 2.0 (MEMR2), MEM Release 1.0c (MEMR1c), and previously internally controlled and released versions of MEMCxP v2.0 and LunarMEM v2.0. Earlier versions of MEM superseded older models of the meteoroid environment such as the Grün model and its derivative, Technical Memo 4527 (hereafter abbreviated as TM 4527) [1]. Prior to the establishment of the NASA Meteoroid Environment Office (MEO), NASA’s meteoroid environment models relied on a simple empirical expression derived from [2], as described in [3] and later in [1]. This expression describes the meteoroid flux incident on a flat plate near 1 au. TM 4527 assumes an isotropic environment, making the orientation of the plate irrelevant [4]. The flux was combined with scale factors to account for the reduction in flux occurring when the Earth shields the spacecraft from a portion of the meteoroid environment and the enhancement in flux due to the focusing effect of Earth’s gravitational field. TM 4527 also introduced a crude, piecewise meteoroid speed distribution with an average velocity of 19 km/s for an orbiting spacecraft based on [5]. Finally, TM 4527 assumed a three-step density distribution in which dust particles smaller than 10−6 g have a density of 2 g/cu cm, micrometeoroids between 10−6 g and 0.01 g have a density of 1 g/cu cm, and meteoroids larger than 0.01 g have a density of 0.5 g/cm3. Thus, the meteoroid model presented in TM 4527 was assembled from multiple independent sources. The model of TM 4527 was also used for years in Space Station risk assessments, and is described in Space Station Specification (SSP) 30425.

Moorhead, A. V.↗

Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X

MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.

Bent, Russell↗

Pilot Delays For Three Cockpit Controllers

Pilot effective delay increases with system delay. Report compares pilot effective time delays measured in simulations of aircraft-control systems equipped with Space Shuttle rotational hand controller and with two versions of conventional stick-type hand controller. Report of interest to those concerned with design of multiple-axis controllers in aircraft, armored vehicles, industrial machinery, and remote manipulators: operator response or delay critical to stable and accurate operation of such systems.

Privoznik, Cynthia M.↗

Location selection for vibration controllers in space crane as adaptive structures

It is assumed that the space crane is vibrating about a known configuration which is reached at the end of some maneuver. For this configuration, r actuator locations are to be determined in order to control the first q of the structural vibration modes of the system optimizing the energy dissipation rate. A modified version of the control stratagem of Chang (1980) is applied using the structural modes of the uncontrolled crane, followed by algorithms for the actuator placement problem.

Lu, L. Y.↗

Discrete-time entropy formulation of optimal and adaptive control problems

The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

Tsai, Yweting A.↗

Advanced Energy Harvesting Control Schemes for Marine Renewable Energy Devices

The Advanced Energy Harvesting Control Schemes for Marine Renewable Energy Devices (Project) investigated, analyzed and modeled advanced turbine control schemes with the objective of increasing the energy harvested by hydrokinetic turbines in turbulent flow. Ocean Renewable Power Company (ORPC) implemented and validated a feedforward controller to increase power capture; and applied and tested the controls on ORPC’s RivGen® Power Systems in Igiugig, Alaska. Assessments of performance improvements were made for the RivGen® in the Igiugig environment and for ORPC’s TidGen® Power System in a reference tidal environment. Annualized Energy Production (AEP) and Levelized Cost of Energy (LCOE) improvements associated with implementation of the recommended control methodology were made for the TidGen® Power System in the DOE reference tidal environment. System Performance Advancement (SPA) goals were selected for the project. SPA targets were to improve Power to Weight Ratio (PWR) and system Availability, with the intention of reducing Levelized Cost of Electricity (LCOE). This project focused primarily reducing in PWR. Reductions in PWR of 25.5% were achieved. Reductions of 20.3% in LCOE were achieved. This project evaluated four types of controllers which were tested in simulation, emulation, a laboratory flume, and the field. The adaptive Kω2 controller performs similarly to the non-adaptive version of the same controller and may be useful in tidal channels where the mean velocity is continually evolving. Trends in simulation were largely verified through experiments, which also provided the opportunity to test assumptions about turbine responsiveness and control resilience to varying scales of turbulence. Laboratory experiments provided an essential stepping stone between simulation and implementation on a field-scale turbine. Experiments also demonstrated that using “energy loss” as a metric to differentiate between well-designed controllers operating at an optimal tip-speed ratio set-point is difficult, which anticipated the outcome from field experiments. The clear message is that the feedforward Kω2 controller out-performs the feedback controllers in almost all aspects and modes of evaluation. The controllers proved a substantial improvement over the baseline performance of the TidGen® turbine, in terms of energy capture. The effects of noise-contaminated angular velocity signals were investigated and validated by simulation as an explanation for the performance limitations observed for TidGen® turbine operations in Eastport, Maine. Measurements of loads performed as part of the laboratory testing indicate that there are limited differences in average axial thrust force between control architectures. This suggests that none of the control strategies are likely to substantially affect loads on the turbine support structure. Velocity measurements during the ORPC RivGen® turbine deployment at Igiugig, Alaska, in 2014 were used to assess the variability of the river flow. Results suggest that the river flow is approximately steady, in the mean sense, at any particular location in the river, with random turbulent fluctuations that are around 10% of the mean flow. The mean flow in the center channel of the river is 2.5 m/s, with reductions near the riverbanks and in the shallows. Spectral analysis and lagged correlation results indicate that temporal fluctuations at a given point are dominated by large scale fluctuations, such that measurements at the turbine location are just as useful for inflow control implementation as upstream measurements. At this site, and likely at many other river sites, flow is generally steady at a given location, but flow varies dramatically between locations, particularly laterally across the river. The primary result is that a lateral change in position of a few meters results in changes to flow speed that far exceed the turbulence fluctuations at any given location. The turbulence is dominated by long time scales. Following final system tests, the RivGen® device was submerged and each evaluated controller was tested across a range of gain/set point values and filter configurations for a minimum of 5 minutes, with longer runs attempted for well-performing cases. In addition to testing controllers during the 2015 deployment season, LGL Alaska Research Associates Inc. (LGL) performed a fish monitoring study in compliance with Alaska Department of Fish and Game fisheries habitat permit for the project. During the season, LGL reviewed 10% of 179 one-hour blocks of footage (6 minutes on the hour) and documented a total of over 1200 fish in the vicinity of the RivGen® device, including over 800 salmon smolt and over 350 adult salmon. No evidence of adverse effects including passage delay by upstream migrating salmon was noted. This is an important result for future deployments and has a direct impact on commercial system designs.

16 TIDAL AND WAVE POWER↗

Soft-Starting Power-Factor Motor Controller

Three-phase power-factor controller with soft start is based on earlier version that does not control starting transients. Additional components serve to turn off "run" command signal and substitute gradual startup command signal during preset startup interval. Improved controller reduces large current surge that usually accompanies starting. Controller applies power smoothly, without causing motor vibrations.

Nola, F. J.↗

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗

Simulation test results for lift/cruise fan research and technology aircraft

A flight simulation program was conducted on the flight simulator for advanced aircraft (FSAA). The flight simulation was a part of a contracted effort to provide a lift/cruise fan V/STOL aircraft mathematical model for flight simulation. The simulated aircraft is a configuration of the Lift/Cruise Fan V/STOL research technology aircraft (RTA). The aircraft was powered by three gas generators driving three fans. One lift fan was installed in the nose of the aircraft, and two lift/cruise fans at the wing root. The thrust of these fans was modulated to provide pitch and roll control, and vectored to provide yaw, side force control, and longitudinal translation. Two versions of the RTA were defined. One was powered by the GE J97/LF460 propulsion system which was gas-coupled for power transfer between fans for control. The other version was powered by DDA XT701 gas generators driving 62 inch variable pitch fans. The flight control system in both versions of the RTA was the same.

Bland, M. P.↗

Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions

Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO 2 ) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO 2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO 2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO 2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.

54 ENVIRONMENTAL SCIENCES↗

Electronic Control Of Slow Rotations

Digital/analog circuit controls both angular position and speed of rotation of motor shaft with high precision. Locks angular position of motor to phase of rotation-command clock signal at binary submultiple of master clock signal. Circuit or modified version used to control precisely position and velocity of robotic manipulator, to control translation mechanism of crystal-growing furnace, to position hands of mechanical clock, or to control angular position and rate of rotation in any of large variety of rotating mechanisms.

Howard, David E.↗

Operators manual for microdensitometer control program densitometer model PDS-1010G (modified). Program trace version 3B (section 3)

The PDS-1010G microdensitometer is run under the control of a PDP-11 program called TRACE. This program gives the operator vary flexible control over the machine functions. Most commands are passed to the computer through either the Tektronix 4010 terminal or the teletype, as selected by the position of the LOCAL/LINE rocker switch above the 4010 keyboard. (LINE places the 4010 in control; LOCAL transfers control to the teletype. In general, the teletype is used when the operator desires a permanent record of the operator-computer dialogue.) A small number of control functions are requested by setting switches on the computer front panel.

Title, A. M.↗

Semispan Test Results of a Conventional High-Lift Common Research Model in Landing Configuration

A 10%-scale high-lift version of the Common Research Model (CRM-HL) was tested in the 14- by 22-Foot Subsonic Tunnel at the NASA Langley Research Center. This research was aimed at providing a representative reference case for comparison with an Active Flow Control (AFC) enabled version of the CRM-HL and to increase the existing experimental database for CFD high-lift prediction. The test was conducted mostly at a freestream Mach number of 0.20. The effects of the engine nacelle, nacelle chine, tufts, small variations in Mach number, hysteresis-associated increasing/decreasing angle of attack, and incoming floor boundary-layer thickness (i.e., thinning by activation of the floor boundary layer removal system) were examined. A prestall lift performance degradation for the CRM-HL configuration was resolved with a properly placed nacelle chine. Surface pressure results are presented in detail for three key variants of CRM-HL — baseline (nacelle on), nacelle off, and nacelle with the most effective chine installation. The presented aerodynamic forces and surface pressures include both with and without the wall correction using the Transonic Wall Interference Correction System (TWICS) method. A limited set of photogrammetry results is also presented to document the model deformation under test conditions.

high-lift↗