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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

MODAL CLASSIFICATION: Processing and Anomaly Detection in a Noisy Vibrational Environment

n this report we summarize the development of a model-based detection scheme capable of the on-line detection of structural anomalies applying both system identification methods to extract a modal model and state estimation/detection methods to both detect an anomaly and locate all affected sensor positions specified by measurement location. Background information evolving from a simple single input/single output (SISO) mechanical system introducing the state-space formulation which leads directly to a multiple input/multiple output (MIMO) state-space formulation is discussed.From that representation the modal state-space model is introduced through an eigenvalue-eigenvector formulation leading to a similarity transformation and complex modes. Next the sampled-data state-space system is introduced leading to discrete state-space systems which provide the basis for the system identification methods to follow.

42 ENGINEERING↗
NASA NTRS2010

Parameterized Linear Longitudinal Airship Model

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

Kulczycki, Eric↗
NASA NTRS2009

Methodologies for Adaptive Flight Envelope Estimation and Protection

This paper reports the latest development of several techniques for adaptive flight envelope estimation and protection system for aircraft under damage upset conditions. Through the integration of advanced fault detection algorithms, real-time system identification of the damage/faulted aircraft and flight envelop estimation, real-time decision support can be executed autonomously for improving damage tolerance and flight recoverability. Particularly, a bank of adaptive nonlinear fault detection and isolation estimators were developed for flight control actuator faults; a real-time system identification method was developed for assessing the dynamics and performance limitation of impaired aircraft; online learning neural networks were used to approximate selected aircraft dynamics which were then inverted to estimate command margins. As off-line training of network weights is not required, the method has the advantage of adapting to varying flight conditions and different vehicle configurations. The key benefit of the envelope estimation and protection system is that it allows the aircraft to fly close to its limit boundary by constantly updating the controller command limits during flight. The developed techniques were demonstrated on NASA s Generic Transport Model (GTM) simulation environments with simulated actuator faults. Simulation results and remarks on future work are presented.

Tang, Liang↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
NASA NTRS1981

The reduced order model problem in distributed parameter systems adaptive identification and control

The basic assumption that a large space structure can be decoupled preceding the application of reduced order active control was considered and alternative solutions to the control of such structures (in contrast to the strict modal control) were investigated. The transfer function matrix from the actuators to the sensors was deemed to be a reasonable candidate. More refined models from multivariable systems theory were studied and recent results in the multivariable control field were compared with respect to theoretical deficiencies and likely problems in application to large space structures.

Johnson, C. R., Jr.↗
NASA NTRS1976

Specification of inputs and instrumentation for flutter testing of multivariable systems

The application of system identification methods in flutter testing of aeroelastic structure is discussed. The accuracy with which flutter parameters are estimated depends upon the test plan and on the algorithms used to reduce the data. The techniques for selecting the kinds and optimal positions of inputs and instrumentation, under typical test constraints, are presented. Identification results for both the input/output transfer function and the value of physical parameters are given. Numerical results on the optimal input spectrum and the accelerometer location for estimating flutter parameters of a two dimensional wing are obtained using these algorithms. Current work on applying system identification methods to high order three dimensional aeroelastic structures is reported.

Gupta, N. K.↗
DOE OSTI2014

Morphometric Comparison of Clavicle Outlines from 3D Bone Scans and 2D Chest Radiographs: A Short-listing Tool to Assist Radiographic Identification of Human Skeletons

This paper describes a computerized clavicle identification system, primarily designed to resolve the identities of unaccounted for US soldiers who fought in the Korean War. Elliptical Fourier analysis is used to quantify the clavicle outline shape from skeletons and postero-anterior antemortem chest radiographs to rank individuals in terms of metric distance. Similar to leading fingerprint identification systems, shortlists of the top matching candidates are extracted for subsequent human visual assessment. Two independent tests of the computerized system using 17 field-recovered skeletons and 409 chest radiographs demonstrate that true positive matches are captured within the top 5% of the sample 75% of the time. These results are outstanding given the eroded state of some field-recovered skeletons and the faintness of the 1950’s photoflurographs. These methods enhance the capability to resolve several hundred cold cases for which little circumstantial information exists and current DNA and dental record technologies cannot be applied.

computer assisted↗
NASA NTRS1997

High Accuracy Evaluation of the Finite Fourier Transform Using Sampled Data

Many system identification and signal processing procedures can be done advantageously in the frequency domain. A required preliminary step for this approach is the transformation of sampled time domain data into the frequency domain. The analytical tool used for this transformation is the finite Fourier transform. Inaccuracy in the transformation can degrade system identification and signal processing results. This work presents a method for evaluating the finite Fourier transform using cubic interpolation of sampled time domain data for high accuracy, and the chirp Zeta-transform for arbitrary frequency resolution. The accuracy of the technique is demonstrated in example cases where the transformation can be evaluated analytically. Arbitrary frequency resolution is shown to be important for capturing details of the data in the frequency domain. The technique is demonstrated using flight test data from a longitudinal maneuver of the F-18 High Alpha Research Vehicle.

Morelli, Eugene A.↗
NASA NTRS2018

Tracking Components

This poster outlines the findings during a 10-week, full-time summer internship at NASA’s Stennis Space Center (SSC) in Mississippi. As an intern with RA10, the Project Management Division of Center Operations Directorate, I contributed to tasks related to the advancement of systems and operations across SSC. My main priority was to optimize the transportation process of work order kits delivered from the Michoud Assembly Facility (MAF) in New Orleans, Louisiana. An example work order kit would include instructions and materials to complete the replacement of a broken light switch. Unfortunately, kits that arrive at SSC often contain incorrect parts, which results in returning to MAF to get the necessary parts. Integrating a wireless tracking and identification system could improve this way of operating by providing a parts lists and kit location. This idea of using wireless technology will essentially cut costs, time and effort. The main objective for this summer is to develop options for affordable tracking and identification systems that can be used across the agency.

Meredith, Shelby↗
DOE OSTI2011

Plasma Modeling Results and shape control improvements for NSTX

New control implementations and dynamics studies on the National Spherical Torus eXperiment (NSTX) are summarized. In particular, strike point (SP) position, X-point height and squareness control, and two new system-identification methods / control-tuning algorithms were put into operation.The PID controller for the SP was tuned by analyzing the step response of the SP position to the poloidal coil currents, employing the Ziegler-Nichols method. The resulting SP controller was successfully employed to achieve the “snowflake” divertor configuration in NSTX. An offline system identification of the plasma response to the control inputs based on ARMAX input-output models was implemented. With this tool, rough estimates of the improvements were realized and several control improvements were identified.An online automatic relay-feedback PID tuning algorithm was implemented, which has the advantage of tuning the controller in one shot, thus optimizing the use of experimental time. Furthermore, using these new capabilities, we implemented LLD scenarios with control for theall four upper/lower/inner/outer SPs and with a combined X-point height, SP radius control. Separately, an independent squareness control was implemented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1988

Orbiter Flying Qualities (OFQ) Workstation user's guide

This project was devoted to the development of a software package, called the Orbiter Flying Qualities (OFQ) Workstation, for working with the OFQ Archives which are specially selected sets of space shuttle entry flight data relevant to flight control and flying qualities. The basic approach to creation of the workstation software was to federate and extend commercial software products to create a low cost package that operates on personal computers. Provision was made to link the workstation to large computers, but the OFQ Archive files were also converted to personal computer diskettes and can be stored on workstation hard disk drives. The primary element of the workstation developed in the project is the Interactive Data Handler (IDH) which allows the user to select data subsets from the archives and pass them to specialized analysis programs. The IDH was developed as an application in a relational database management system product. The specialized analysis programs linked to the workstation include a spreadsheet program, FREDA for spectral analysis, MFP for frequency domain system identification, and NIPIP for pilot-vehicle system parameter identification. The workstation also includes capability for ensemble analysis over groups of missions.

Myers, Thomas T.↗
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 NTRS1988

Extension and validation of a method for locating damaged members in large space trusses

The damage location approach employs the control system capabilities for the structure to test the structure and measure the dynamic response. The measurements are then used in a system identification algorithm to produce a model of the damaged structure. The model is compared to one for the undamaged structure to find regions of reduced stiffness which indicate the location of damage. Kabe's 3,4 stiffness matrix adjustment method was the central identification algorithm. The strength of his method is that, with minimal data, it preserves the representation of the physical connectivity of the structure in the resulting model of the damaged truss. However, extensive storage and computational effort were required as a result. Extension of the damage location method to overcome these problems is the first part of the current work. The central system identification algorithm is replaced with the MSMT method of stiffness matrix adjustment which was previously derived by generalizing an optimal-update secant method form quasi-Newton approaches for nonlinear optimization. Validation of the extended damage location method is the second goal.

Smith, Suzanne Weaver↗
NASA NTRS1995

Dissipative rendering and neural network control system design

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.

Gonzalez, Oscar R.↗
DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗
DOE OSTI2024

Development of real-time density feedback control on MAST-U in L-mode

In this paper we report on the development and demonstration of density feedback control for MAST-U. Sinusoidal perturbations are used to measure the frequency response from a deuterium gas valve (actuator) to line-integrated core electron density measured by the interferometer (sensor). In the frequency range relevant for control design, only two system-identification experiments were needed to regress a first-order dynamic model. This control-oriented model informs the offline design of a proportional integral controller with the established loop-shaping controller design method. After offline verification of the controller implementation, control is demonstrated by experimentally tracking a staircase reference for the line-integrated electron density. This paper demonstrates the efficiency of controller design using system-identification and loop-shaping, providing reliable density control for MAST-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Mode Shape Estimation Algorithms Under Ambient Conditions: A Comparative Review

Abstract—This paper provides a comparative review of five existing ambient electromechanical mode shape estimation algorithms, i.e., the Transfer Function (TF), Spectral, Frequency Domain Decomposition (FDD), Channel Matching, and Subspace Methods. It is also shown that the TF Method is a general approach to estimating mode shape and that the Spectral, FDD, and Channel Matching Methods are actually special cases of it. Additionally, some of the variations of the Subspace Method are reviewed and the Numerical algorithm for Subspace State Space System IDentification (N4SID) is implemented. The five algorithms are then compared using data simulated from a 17-machine model of the Western Electricity Coordinating Council (WECC) under ambient conditions with both low and high damping, as well as during the case where ambient data is disrupted by an oscillatory ringdown. The performance of the algorithms is compared using the statistics from Monte Carlo Simulations and results from measured WECC data, and a discussion of the practical issues surrounding their implementation, including cases where power system probing is an option, is provided. The paper concludes with some recommendations as to the appropriate use of the various techniques. Index Terms—Electromechanical mode shape, small-signal stability, phasor measurement units (PMU), system identification, N4SID, subspace.

Dosiek, Luke↗