Search NASA⌕ Search

SEARCH · Search NASA

Results for “Adaptive systems”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Adaptive control system for line-commutated inverters

A control system for a permanent magnet motor driven by a multiphase line commutated inverter is provided with integration for integrating the back EMF of each phase of the motor. This is used in generating system control signals for an inverter gate logic using a sync and firing angle (alpha) control generator connected to the outputs of the integrators. A precision full wave rectifier provides a speed control feedback signal to a phase delay rectifier via a gain and loop compensation circuit and to the integrators for adaptive control of the attenuation of low frequencies by the integrators as a function of motor speed. As the motor speed increases, the attenuation of low frequency components by the integrators is increased to offset the gain of the integrators to spurious low frequencies.

Dolland, C. R.↗
NASA NTRS2012

Intelligent Optical Systems Using Adaptive Optics

Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

Clark, Natalie↗
NASA NTRS2012

Results from the PALM-3000 High-Order Adaptive Optics System

The first of a new generation of high actuator density AO systems developed for large telescopes, PALM-3000 is optimized for high-contrast exoplanet science but will support operation with natural guide stars as faint as V approx. 18. PALM-3000 began commissioning in June 2011 on the Palomar 200" telescope and has to date over 60 nights of observing. The AO system consists of two Xinetics deformable mirrors, one with 66 by 66 actuators and another with 21 by 21 actuators, a Shack-Hartman WFS with four pupil sampling modes (ranging from 64 to 8 samples across the pupil), and a full vector matrix multiply real-time system capable of running at 2KHz frame rates. We present the details of the completed system, and initial results. Operating at 2 kHz with 8.3cm pupil sampling on-sky, we have achieved a K-band Strehl ratio as high as 84% in approx.1.0 arcsecond visible seeing.

Palomar↗
NASA NTRS2011

Experimental Study of a Membrane Antenna Surface Adaptive Control System

Due to their ultra lightweight and high packaging efficiency, membrane reflectors are getting more and more attentions for mission architectures that need extremely large inspace deployable antennas. However how to maintain the surface shape of a membrane reflector to the instrument precision requirements is a very challenging problem. This experimental study investigated using PVDF membrane piezoelectric material as actuators to control the surface figures of membrane reflectors. The feasibility of this approach is demonstrated by several sets of test results.

packaging↗
NASA NTRS2009

Implementation of an Adaptive Controller System from Concept to Flight Test

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a "floating limiter" (FL) concept that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly "floating" and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually "hit" the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗
NASA NTRS1972

Survey of adaptive control using Liapunov design

A survey was made of the literature devoted to the synthesis of model-tracking adaptive systems based on application of Liapunov's second method. The basic synthesis procedure is introduced and a critical review of extensions made to the theory since 1966 is made. The extensions relate to design for relative stability, reduction of order techniques, design with disturbance, design with time variable parameters, multivariable systems, identification, and an adaptive observer.

Lindorff, D. P.↗
NASA NTRS1973

Synthesis of oscillating adaptive feedback systems

A synthesis theory is developed which allows system design to proceed from practical specifications on system command and/or disturbance response to a design which is very nearly optimal in terms of feedback sensor noise effects. The approach taken is to replace the nonlinear element by a mean square error minimizing approximation (dual-input describing function), and then use linear frequency domain synthesis techniques subject to additional constraints imposed by the limit cycle and the approximator. Synthesis techniques are also developed for a similar system using an externally excited oscillating signal with the above approach. The results remove the design of the systems considered from the realm of simulation and experimentation, permitting true synthesis and the optimization that accompanies it.

Smay, J. W.↗
NASA NTRS1996

Adaptive Fuzzy Systems in Computational Intelligence

In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

Berenji, Hamid R.↗
NASA NTRS2003

Development of Methodologies for IV and V of Neural Networks

Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

Taylor, Brian↗
NASA NTRS2005

Telescope Wavefront Aberration Compensation with a Deformable Mirror in an Adaptive Optics System

With the goal of reducing the surface wavefront error of low-cost multi-meter-diameter mirrors from about 10 waves peak-to-valley (P-V), at lpm wavelength, to approximately 1-wave or less, we describe a method to compensate for slowly varying wavefront aberrations of telescope mirrors. A deformable mirror is utilized in an active optical compensation system. The kMS wavefront error of a 0.3m telescope improved to 0.05 waves (0.26 waves P-V) from the original value of 1.4 waves RMS (6.5 waves P-V), measured at 633nm, and the Strehl ratio improved to 89% from the original value of 0.08%.

active optics↗
NASA NTRS2007

Communication system with adaptive noise suppression

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

Kozel, David↗
NASA NTRS2008

Adaptive Flight Control for Aircraft Safety Enhancements

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.

Nguyen, Nhan T.↗
NASA NTRS2016

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Gregory, Irene M.↗
NASA NTRS1970

Skylab Operations Handbook: Orbital Workshop (OWS), Airlock Module (AM), Multiple Docking Adapter (MDA): Systems Descriptions - Volume 1

The Skylab Program consists of three low-earth-orbit missions of the Orbital Assembly (OA) (figure 1.0-1), extending over.an a-month period. The OA consists of the CSM docked to the Saturn Workshop.(SWS). This handbook describes the systems for three of the four major components of the SWS (OWS, AM, and MDA), and also discusses significant interfaces with the Instrument Unit (IU), ATM, and CSM. The other major component of the SWS, the ATM, is treated separately in its own handbook. The OWS, AM, MDA, ATM Deployment Assembly (ATM-DA), Fixed Airlock Shroud (FAS), Payload Shroud (PS), and IU are addressed throughout this document as individual modules from a structural standpoint only. Although normally considered a part of the launch vehicle, the IU is treated in this document as part of the SWS because of its function in preparing the SWS for orbital operation. Section 1.0 describes vehicle and mission configurations of the Skylab program and provides general descriptions of the various systems. Section 2.0 provides detailed systems data covering system interfaces, functional description, subsystems and major components description, component operation, failure modes, performance and design data, operational limitations and restrictions, and instrumentation, and briefly outlines the experiments. Section 3.0 contains illustrations of all panels and identifies the controls and displays, panels, reference designators, nomenclature, functions, circuit breakers, and power sources. The Table of Contents lists in order of appearance all sections, subsections, major paragraphs, illustrations, and tables and provides their respective page locations. Appendix A defines the abbreviations and acronyms employed throughout this handbook, and Appendix B explains the symbols used. Appendix C is a locator index that references component controls contained in Section 3.0. Appendix D is an alphabetical index of paragraph headings, illustrations, and tables, according to the key word, with applicable page numbers. Additional items of significance to the user have been included in the index. The technical level to which this document is written assumes the reader to have general knowledge of engineering terms and principles.

West, W. D.↗