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At least 667 records · Page 37

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NASA NTRS2016

Adaptive Modal Identification for Flutter Suppression Control

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Aeroelasticity↗

NASA NTRS1986

Studies of modal identification performance using hybrid data

Modal identification accuracy can be affected significantly in practice by high modal density and nonlinearities. It may be difficult to determine the true number of modes, and many of the identified mode shapes may be questionable. Results can vary considerably using different analysis techniques. This paper introduces a new method for studying modal identification performance under such circumstances. A difficult set of test data from an erectable truss structure was modified numerically by adding two artificial modes with known parameters. These 'hybrid data' were then analyzed with the Polyreference technique and the Eigensystem Realization Algorithm (ERA). Identification performance is studied by comparing the identified modal parameters for the artificial modes with their known values.

Pappa, Richard S.↗

NASA NTRS1985

Structural analysis model validation using modal test data

The design of a structure which can survive a prescribed dynamic environment is generally based on the use of an analytical model of the structure. The modal test is employed to verify the analytical model. This paper is concerned with the involved validation process, taking into account modal test results from realistic complex spacecraft structural systems as examples to demonstrate the proposed validation procedure. Attention is given to a load analysis model definition, a pretest analysis and test/analysis model, and the correlation parameters. Coordinate transformation is considered along with mode identification, frequency orthogonality, effective mass, mode shape, local kinetic energy, modal force, strain energy, and modal forces by acceleration measurements. Two examples are used to illustrate the procedure.

Chen, J.-C.↗

NASA NTRS1989

An enhanced mode shape identification algorithm

A mode shape identification algorithm is developed which is characterized by a low sensitivity to measurement noise and a high accuracy of mode identification. The algorithm proposed here is also capable of identifying the mode shapes of structures with significant damping. The combined results indicate that mode shape identification is much more dependent on measurement noise than identification of natural frequencies. Accurate detection of modal parameters and mode shapes is demonstrated for modes with damping ratios exceeding 15 percent.

Roemer, Michael J.↗

NASA NTRS1992

A consistent-mode indicator for the eigensystem realization algorithm

A new method is described for assessing the consistency of model parameters identified with the Eigensystem Realization Algorithm (ERA). Identification results show varying consistency in practice due to many sources, including high modal density, nonlinearity, and inadequate excitation. Consistency is considered to be a reliable indicator of accuracy. The new method is the culmination of many years of experience in developing a practical implementation of the Eigensystem Realization Algorithm. The effectiveness of the method is illustrated using data from NASA Langley's Controls-Structures-Interaction Evolutionary Model.

Pappa, Richard S.↗

NASA NTRS1996

Automation of Command and Data Entry in a Glovebox Work Volume: An Evaluation of Data Entry Devices

The present study was designed to examine the human-computer interface for data entry while performing experimental procedures within a glovebox work volume in order to make a recommendation to the Space Station Biological Research Project for a data entry system to be used within the Life Sciences Glovebox. Test subjects entered data using either a manual keypad, similar to a standard computer numerical keypad located within the glovebox work volume, or a voice input system using a speech recognition program with a microphone headset. Numerical input and commands were programmed in an identical manner between the two systems. With both electronic systems, a small trackball was available within the work volume for cursor control. Data, such as sample vial identification numbers, sample tissue weights, and health check parameters of the specimen, were entered directly into procedures that were electronically displayed on a video monitor within the glovebox. A pen and paper system with a 'flip-chart' format for procedure display, similar to that currently in use on the Space Shuttle, was used as a baseline data entry condition. Procedures were performed by a single operator; eight test subjects were used in the study. The electronic systems were tested under both a 'nominal' or 'anomalous' condition. The anomalous condition was introduced into the experimental procedure to increase the probability of finding limitations or problems with human interactions with the electronic systems. Each subject performed five test runs during a test day: two procedures each with voice and keypad, one with and one without anomalies, and one pen and paper procedure. The data collected were both quantitative (times, errors) and qualitative (subjective ratings of the subjects).

Steele, Marianne K.↗

NASA NTRS2006

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

Kukreja, Sunil L.↗

NASA NTRS2012

A13K-0336: Airborne Multi-Wavelength High Spectral Resolution Lidar for Process Studies and Assessment of Future Satellite Remote Sensing Concepts

NASA Langley recently developed the world's first airborne multi-wavelength high spectral resolution lidar (HSRL). This lidar employs the HSRL technique at 355 and 532 nm to make independent, unambiguous retrievals of aerosol extinction and backscatter. It also employs the standard backscatter technique at 1064 nm and is polarization-sensitive at all three wavelengths. This instrument, dubbed HSRL-2 (the secondgeneration HSRL developed by NASA Langley), is a prototype for the lidar on NASA's planned Aerosols- Clouds-Ecosystems (ACE) mission. HSRL-2 completed its first science mission in July 2012, the Two-Column Aerosol Project (TCAP) conducted by the Department of Energy (DOE) in Hyannis, MA. TCAP presents an excellent opportunity to assess some of the remote sensing concepts planned for ACE: HSRL-2 was deployed on the Langley King Air aircraft with another ACE-relevant instrument, the NASA GISS Research Scanning Polarimeter (RSP), and flights were closely coordinated with the DOE's Gulfstream-1 aircraft, which deployed a variety of in situ aerosol and trace gas instruments and the new Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). The DOE also deployed their Atmospheric Radiation Measurement Mobile Facility and their Mobile Aerosol Observing System at a ground site located on the northeastern coast of Cape Cod for this mission. In this presentation we focus on the capabilities, data products, and applications of the new HSRL-2 instrument. Data products include aerosol extinction, backscatter, depolarization, and optical depth; aerosol type identification; mixed layer depth; and rangeresolved aerosol microphysical parameters (e.g., effective radius, index of refraction, single scatter albedo, and concentration). Applications include radiative closure studies, studies of aerosol direct and indirect effects, investigations of aerosol-cloud interactions, assessment of chemical transport models, air quality studies, present (e.g., CALIPSO) and future (e.g., EarthCARE) satellite calibration/validation, and development/assessment of advanced retrieval techniques for future satellite applications (e.g., lidar+polarimeter retrievals of aerosol and cloud properties). We will also discuss the relevance of HSRL-2 measurement capabilities to the ACE remote sensing concept.

Hostetler, Chris A.↗

NASA NTRS1986

Computational methods for the identification of spatially varying stiffness and damping in beams

A numerical approximation scheme for the estimation of functional parameters in Euler-Bernoulli models for the transverse vibration of flexible beams with tip bodies is developed. The method permits the identification of spatially varying flexural stiffness and Voigt-Kelvin viscoelastic damping coefficients which appear in the hybrid system of ordinary and partial differential equations and boundary conditions describing the dynamics of such structures. An inverse problem is formulated as a least squares fit to data subject to constraints in the form of a vector system of abstract first order evolution equations. Spline-based finite element approximations are used to finite dimensionalize the problem. Theoretical convergence results are given and numerical studies carried out on both conventional (serial) and vector computers are discussed.

Banks, H. T.↗

NASA NTRS1985

Space station configuration and flight dynamics identification

The Space Station will be assembled in low earth orbit by a combination of deployable and space erectable modules that are progressively integrated during successive flights of the Shuttle. The crew assisted space construction will result in a configuration which is a large scale composite of structural elements having connectivity with a wide range of possible end conditions and imprecisely known dynamic characteristics. The generic applications of Flight Dynamics Identification to the candidate Space Station configurations currently under consideration are described. Identification functions are categorized, and the various methods for extracting parameter estimates are correlated with the sensing of parameter estimates are correlated with the sensing of specific characteristics of interest to both engineering subsystems and users of the Station's commercial and scientific facilities. Onboard implementation architecture and constraints are discussed from the viewpoint of maximizing integration of the Identification process with the flight subsystem's data and signal flow.

Metter, E.↗

NASA NTRS2022

The Mass Change Designated Observable Study: Overview and Results

The 2017–2027 United States National Academy of Sciences Decadal Survey (DS) for Earth Science and Applications from Space identified Mass Change (MC) as one of five Designated Observables (DOs) having the highest priority in terms of Earth observations required to advance Earth system science over the next decade. In response to this designation, NASA initiated several multi-center studies, with the goal of recommending observing system architectures for each DO for implementation within this decade. This paper provides an overview of the Mass Change Designated Observable (MCDO) Study along with key findings. The study process included: (a) generation of a Science and Applications Traceability Matrix (SATM) that maps required measurement parameters to the DS Science and Applications Objectives; (b) identification of three architecture classes relevant for measuring mass change: Precise Orbit Determination (POD), Satellite-Satellite-Tracking (SST) and Gravity Gradiometry (GG), along with variants within each architecture class; and (c) creation of a Value Framework process that considers science value, cost, risk, schedule, and partnership opportunities, to identify and recommend high value observing systems for further in-depth study. The study team recommended the implementation of an SST architecture, and identified variants that simultaneously (a) satisfy the baseline measurement parameters of the SATM; (b) maximize the probability of providing overlap with the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission currently in operation, accelerating science return from both missions; and (c) provide a pathway towards substantial improvements in resolution and accuracy of mass change data products relative to the program of record.

D N Wiese↗

NASA NTRS1972

Optimal inputs for system identification

Identification criteria are presented for linear dynamic systems with and without process noise. With process noise, the state equations are replaced by the Kalman filter equations. If the identification performance index is expanded in a Taylor's series with respect to the parameters to be identified, then maximizing the weighting factor of the quadratic term with respect to the inputs will insure that an identification algorithm will converge more rapidly and to a more accurate result than with nonoptimal inputs. The expectation of this weighting factor is the Fisher information matrix, and its inverse is a lower bound for the covariance of the parameters. Direct and indirect methods of calculating the information matrix are presented for systems with and without process noise.

Reid, D. B.↗

NASA NTRSDate not supplied

System Identification of Flexible Aircraft: Lessons Learned from the X-56A Phase 1 Flight Tests

The X-56A Multi-Utility Technology Testbed (MUTT) is a subscale airplane that was de-signed as an experimental flight research platform for improving aeroelastic modeling and control technologies. The Phase 1 flight tests, conducted from 2017 to 2019 at the NASA Arm-strong Flight Research Center (AFRC), included 39 flights and approximately 1000 research maneuvers, some of which demonstrated stable closed-loop flight beyond the open-loop flutter speed. This paper summarizes the system identification effort to extract nondimensional stability and control derivatives from the flight test data for constructing aeroelastic models of the flight dynamics. Topics discussed include instrumentation, experiment design, model postulation and reduction, parameter estimation, and others. Throughout the paper, unique challenges for the identification of flexible aircraft, practical aspects of the analysis, and lessons learned are presented.

Jared A Grauer↗

NASA NTRS1981

On matching the systems identification technique to the particular application

Several maximum likelihood and multiple regression parameter estimation programs are currently being used at the Langley Research Center of the NASA to analyze aircraft flight test data. Based on this wealth of experience, the pertinent features of these programs are investigated and some of the difficulties involved in their use are discussed. By comparing computational time, data requirements and accuracy needed, a strategy for determining which program can be used to the best advantage of the flight test engineer is discussed.

Suit, W. T.↗

NASA NTRS1984

Biophysical and spectral modeling for crop identification and assessment

The development of a technique for estimating all canopy parameters occurring in a canopy reflectance model from the measured canopy reflectance data is summarized. The Suits and the SAIL model for a uniform and homogeneous crop canopy were used to determine if the leaf area index and the leaf angle distribution could be estimated. Optimal solar/view angles for measuring CR were also investigated. The use of CR in many wavelengths or spectral bands and of linear and nonlinear transforms of CRs for various solar/view angles and various spectral bands is discussed as well as the inversion of rediance data inside the canopy, angle transforms for filtering out terrain slope effects, and modification of one dimensional models.

Goel, N. S.↗

NASA NTRS1972

Bounded state space

This investigation is divided functionally into three different areas: (1) study of bounded state space, (2) nonlinear smoothing theory, and (3) system identification. (1) Study of bounded state space: necessary and sufficient conditions for an optimal control are obtained for a bounded state space optimal control problem. The difficulty of determining the so-called jump conditions is eliminated; however, the problem of determining the points where the response either enters or leaves the boundary still remains unsolved. (2) Nonlinear smoothing theory: nonlinear fixed-interval, fixed-point and fixed-lag smoothing of a random signal generated by a stochastic differential equation are investigated. Results on the asymptotic stability of a linear constant-parameter fixed-interval smoothing filter are obtained. (3) System identification: a particular stochastic modelling problem is solved. An Ito stochastic integral equation is used to mathematically model a black box having multiple inputs and multiple outputs. A new method for identifying system parameters is presented.

Eyman, E. D.↗

NASA NTRS1978

Results of piloted simulator studies of fighter aircraft at high angles of attack

The experience gained at the NASA Langley Research Center during the application of simulator techniques to high angle of attack flight conditions for several current fighters is discussed. The discussion includes (1) the simulator hardware, (2) requirements for static and dynamic aerodynamic data inputs, (3) evaluation procedures, (4) correlation with flight, and (5) the effects of dynamic stability parameters. Results obtained with the simulator technique have correlated well with flight test experience, resulting in early identification of potential problems, identification of critical flight conditions, and solutions to various deficiencies in stability and control characteristics. Dynamic stability parameters, results indicate that certain parameters can have a large influence on the flying qualities and tactical effectiveness of fighters at high angles of attack.

Chambers, J. R.↗

NASA NTRS1983

Parameter testing for lattice filter based adaptive modal control systems

For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.

Sundararajan, N.↗