Optimum prefiltering in sampled data systems with read-in jitter.
Simultaneous optimization of presampling filter and postsampling linear filter in sample data systems with read-in jitter
SEARCH · Search NASA
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.
Simultaneous optimization of presampling filter and postsampling linear filter in sample data systems with read-in jitter
Special purpose rapid computer for providing an on-line solution to the sampled-data time-optimal- control problem in which inputs are subjected to amplitude constraints
Sampled-data regulator for investigating both steady-state and transient responses of respiratory system of humans to reduced oxygen at fixed levels of carbon dioxide
Sampled data regulator for maintenance of constant alveolar carbon dioxide during steady state and transient ventilatory responses to hypoxic stimulation
Algorithm for solving Popov stability criterion applied to sampled data systems
Approximate root locus method in S plane for sampled data systems, mapping constant frequency and constant damping ratio loci onto W plane
A comprehensive sampled data analysis of a computer-controlled manipulator is presented in terms of root loci for gain selection and transient responses to step input functions. All parameter values and their derivations where applicable were tabulated. The analysis, while quite specific, uses normalized gain parameters, which allows the results to be applied to any similar system regardless of individual hardware parameter values.
Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10 -5 to 10 -1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.
The dynamics of the Large Space Telescope (LST) control system were studied in order to arrive at a simplified model for computer simulation without loss of accuracy. The frictional nonlinearity of the Control Moment Gyroscope (CMG) Control Loop was analyzed in a model to obtain data for the following: (1) a continuous describing function for the gimbal friction nonlinearity; (2) a describing function of the CMG nonlinearity using an analytical torque equation; and (3) the discrete describing function and function plots for CMG functional linearity. Preliminary computer simulations are shown for the simplified LST system, first without, and then with analytical torque expressions. Transfer functions of the sampled-data LST system are also described. A final computer simulation is presented which uses elements of the simplified sampled-data LST system with analytical CMG frictional torque expressions.
Sampled-data theory, using the Z transformation, is applied to the design of a digital controller for an aircraft-altitude autopilot. Particular attention is focused on the sensitivity of the design to parameter variations and the abruptness of the response, that is, the normal acceleration required to carry out a transient maneuver. Consideration of these two characteristics of the system has shown that the finite settling time design method produces an unacceptable system, primarily because of the high sensitivity of the response to parameter variations, although abruptness can be controlled by increasing the sampling period. Also demonstrated is the importance of having well-damped poles or zeros if cancellation is attempted in the design methods. A different method of smoothing the response and obtaining a design which is not excessively sensitive is proposed, and examples are carried through to demonstrate the validity of the procedure. This method is based on design concepts of continuous systems, and it is shown that if no pole-zero cancellations are allowed in the design, one can obtain a response which is not too abrupt, is relatively insensitive to parameter variations, and is not sensitive to practical limits on control-surface rate. This particular design also has the simplest possible pulse transfer function for the digital controller. Simulation techniques and root loci are used for the verification of the design philosophy.
Analog computer simulation to assess random sampling interval effects on sampled data model of human operator
Special purpose computer for implementing programmable digital filter used in sampled data control systems
System controller for digital data sampling modules
Application of Z-transforms to sampled-data systems
Program performs general analysis of linear and continuous, discrete and sampled-data systems using state-variable techniques. Program is especially suited analysis of linearized control system problems. It also can be used to model system described by combination of differential equations and Laplace transform blocks, such as aircraft control system.
Digital controller design for forward and feedback loops of multivariable sample-data control systems
Programmed search and gradient search methods for determination of sampling intervals in synthesis of sampled data models of human operators
Discrete filter for determining autocorrelation functions of internal disturbances in sampled data control system during operation