QUALITY PROGRAM EVALUATION PROCEDURES
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Results for “Identification problem”
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 wideband digital correlator.
Envelope polarity coincidence crosscorrelator for detection and identification problems involving weak wideband microwave signals
MICROWAVE TRANSMISSION↗
New technique for optimal smoothing of data
Recursive method for the optimal smoothing of data has numerical superiority and is more easily understood in terms of physical reasoning than earlier methods. Using a Kalman filter, the smoothing technique, applied to a nonlinear parameter identification problem, is useful in those situations where linearization about a reference solution is valid.
Fraser, D. C.↗
He sub 2 super plus in the topside ionosphere.
He ion identification problems in topside ionosphere, suggesting confirmation by N ion current modulation curves and rocket measurements of ion scale heights
Banks, P. M.↗
The process of problem finding
Managerial practices of problem identification, discussing research study in operating division of large corporation
Pounds, W. F.↗
A parameter identification method combining acceleration search /Partan/ and continuous parameter tracking.
A parameter identification method is presented which combines the best features of two well-established, existing methods: Continuous Parameter Tracking and Acceleration Search (Partan). In this paper the equations are developed for the general n-parameter identification problem, and results are given for a specific two parameter application.
Jackson, G. A.↗
Doppler frequency in interplanetary radar and general relativity
The change of frequency of an interplanetary radar signal sent from the earth to another planet or to a space probe is worked out according to general relativity. The Schwarzschild spacetime is employed and its null geodesics control the motion of the signals. Exact Doppler frequency formulas are derived for one-way and two-way radar in terms of an arbitrary Schwarzschild radial coordinate. A reduction to the special relativity case is used to interpret the formulas in terms of the relative radial velocity of emitter and target. The general relativity corrections are worked out approximately for each of three possible Schwarzschild radial coordinates, and a numerical example is given. The amount of the correction is different according as one or the other of the Schwarzschild coordinates is identified with the radius vector deduced from classical celestial mechanics. The identification problem is discussed.
Mcvittie, G. C.↗
Identification of aircraft stability and control parameters using multilevel, hierarchical estimation
Previous attempts to identify aircraft stability and control derivatives from flight test data, using three-degrees-of-freedom (3-DOF) longitudinal or lateral-directional perturbation-equations-of-motion models, suffer from the disadvantage that the coupling between the longitudinal and lateral-directional dynamics has been ignored. In this paper the identification of aircraft stability parameters is accomplished using a more accurate 6-DOF model which includes this coupling. Hierarchical system identification theory is used to reduce the computational effort involved. The 6-DOF system of equations is decomposed into two 3-DOF subsystems, one for the longitudinal dynamics and the other for the lateral-directional dynamics. The two subsystem parameter identification processes are then coordinated in such a way that the overall system parameter identification problem is solved.
Fry, C. M.↗
Parameter estimation using an a posteriori criterion
A procedure for estimating noise statistics as well as system model parameters, based on a maximum likelihood criterion, has been successfully applied to a number of aircraft parameter-identification problems. In the present investigation, an a posteriori criterion is examined for use in such an application, when it is desired to model process noise. The criteria lead to identical results when there is no process noise.
Bach, R. E., Jr.↗
Adaptive sequential estimation with applications
A sequential estimator is presented and demonstrated which successfully tracks the system state and model errors in the presence of significant and unpredictable system or environmental variations. This adaptive estimation concept is shown to lead to a new and attractive approach to parameter identification problems. Simulation results are presented in an orbit determination problem, where the estimator tracks the orbit and unmodeled accelerations due to errors in the geopotential model. Some results in a re-entry trajectory estimation problem are also summarized.
Jazwinski, A. H.↗
Adaptive sequential estimation with applications
A sequential estimator is presented and demonstrated which successfully tracks the system state and model errors in the presence of significant and unpredictable system or environmental variations. This adaptive estimation concept is shown to lead to a new and attractive approach to parameter identification problems. Simulation results are presented in an orbit determination problem and in a reentry trajectory estimation problem.
Jazwinski, A. H.↗
Urban development applications project. Urban technology transfer study
Technology transfer is defined along with reasons for attempting to transfer technology. Topics discussed include theoretical models, stages of the innovation model, communication process model, behavior of industrial organizations, problem identification, technology search and match, establishment of a market mechanism, applications engineering, commercialization, and management of technology transfer.
Source record↗
Regions of constrained maximum likelihood parameter identifiability
This short paper considers the parameter-identification problem of general discrete-time, nonlinear, multiple input-multiple output dynamic systems with Gaussian white distributed measurement errors. Knowledge of the system parameterization is assumed to be available. Regions of constrained maximum likelihood (CML) parameter identifiability are established. A computation procedure employing interval arithmetic is proposed for finding explicit regions of parameter identifiability for the case of linear systems.
Lee, C.-H.↗
Regions of constrained maximum likelihood parameter identifiability
This paper considers the parameter identification problem of general discrete-time, nonlinear, multiple-input/multiple-output dynamic systems with Gaussian-white distributed measurement errors. Knowledge of the system parameterization is assumed to be known. Regions of constrained maximum likelihood (CML) parameter identifiability are established. A computation procedure employing interval arithmetic is proposed for finding explicit regions of parameter identifiability for the case of linear systems. It is shown that if the vector of true parameters is locally CML identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the CML estimation sequence will converge to the true parameters.
Lee, C.-H.↗
Implicit model following and parameter identification of unstable aircraft
A transformation in the s-plane is described which has utility in implicit model-following optimal control design application and in estimation or parameter identification problems. The objective of the transformation is, for the control problem, to achieve an unstable closed-loop system, and, for the estimation problem, to alleviate algorithm convergence problems that may arise in identifying unstable systems. For the control problem, the transformation is a shift along the real (sigma) axis of the plant and model poles and zeros. This transformation is shown to be equivalent to a modified performance index but offers the advantage of compatibility with existing optimal control solution algorithms. For the estimation problem, the data are multiplied by an exponential function and the assumed measurement and process noise covariances are appropriately modified. Examples of both control and estimation applications are presented.
Lebacqz, J. V.↗
Stochastic control system parameter identifiability
The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.
Lee, C. H.↗
Self-tuning regulators for multicyclic control of helicopter vibration
A class of algorithms for the multicyclic control of helicopter vibration and loads is derived and discussed. This class is characterized by a linear, quasi-static, frequency-domain model of the helicopter response to control; identification of the helicopter model by least-squared-error or Kalman filter methods; and a minimum variance or quadratic performance function controller. Previous research on such controllers is reviewed. The derivations and discussions cover the helicopter model; the identification problem, including both off-line and on-line (recursive) algorithms; the control problem, including both open-loop and closed-loop feedback; and the various regulator configurations possible within this class. Conclusions from analysis and numerical simulations of the regulators provide guidance in the design and selection of algorithms for further development, including wind tunnel and flight tests.
Johnson, W.↗
Phase shift errors in the theory and practice of surface intensity measurements
The surface acoustical intensity method (sometimes known as the microphone-accelerometer cross-spectral method) is a relatively new noise source/path identification tool. Several researchers have had difficulties implementing this method because of instrumentation phase mis-match. A simple technique for measuring and correcting instrumentation phase mis-match has been developed. This new technique has been tested recently on a noise source identification problem of practical interest. The results of the experiments indicate that the surface acoustic intensity method produces reliable data and can be applied to a variety of noise source/path problems.
Mcgary, M. C.↗