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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A method for exponential propagation of large systems of stiff nonlinear differential equations

A new time integrator for large, stiff systems of linear and nonlinear coupled differential equations is described. For linear systems, the method consists of forming a small (5-15-term) Krylov space using the Jacobian of the system and carrying out exact exponential propagation within this space. Nonlinear corrections are incorporated via a convolution integral formalism; the integral is evaluated via approximate Krylov methods as well. Gains in efficiency ranging from factors of 2 to 30 are demonstrated for several test problems as compared to a forward Euler scheme and to the integration package LSODE.

Friesner, Richard A.↗
NASA NTRS1976

Recursive identification and tracking of parameters for linear and non-linear multivariable systems

The problem of identifying constant and variable parameters in multi-input, multi-output, linear and nonlinear systems is considered, using the maximum likelihood approach. An iterative algorithm, leading to recursive identification and tracking of the unknown parameters and the noise covariance matrix, is developed. Agile tracking and accurate and unbiased identified parameters are obtained. Necessary conditions for a globally asymptotically stable identification process are provided; the conditions proved to be useful and efficient. Among different cases studied, the stability derivatives of an aircraft were identified and some of the results are shown as examples.

Sidar, M.↗
NASA NTRS1987

Nonlinear input-output systems

Necessary and sufficient conditions that the nonlinear system dot-x = f(x) + ug(x) and y = h(x) be locally feedback equivalent to the controllable linear system dot-xi = A xi + bv and y = C xi having linear output are found. Only the single input and single output case is considered, however, the results generalize to multi-input and multi-output systems.

Hunt, L. R.↗
NASA NTRS1980

Noise adding radiometer performance analysis

The DSN noise adding radiometer (NAR) measurement accuracy is analyzed. The NAR capability is part of the precision power monitor function recently introduced in the DSN. The potential system noise temperature measurement accuracy is estimated to be about 1.5% with the 1 kelvin noise diode. Performance verification requires comparison noise temperature measurements with the manual Y factor method and routine monitoring of critical elements in the NAR system such as system linearity and noise diode calibration. A technique is presented to calibrate and reduce the effects of the receiving system nonlinearity. Unsatisfactory performance or degradation of these critical NAR elements would require appropriate system upgrading.

Stelzried, C.↗
NASA NTRS1996

Time Varying Compensator Design for Reconfigurable Structures Using Non-Collocated Feedback

Analysis and synthesis tools are developed to improved the dynamic performance of reconfigurable nonminimum phase, nonstrictly positive real-time variant systems. A novel Spline Varying Optimal (SVO) controller is developed for the kinematic nonlinear system. There are several advantages to using the SVO controller, in which the spline function approximates the system model, observer, and controller gain. They are: The spline function approximation is simply connected, thus the SVO controller is more continuous than traditional gain scheduled controllers when implemented on a time varying plant; ft is easier for real-time implementations in storage and computational effort; where system identification is required, the spline function requires fewer experiments, namely four experiments; and initial startup estimator transients are eliminated. The SVO compensator was evaluated on a high fidelity simulation of the Shuttle Remote Manipulator System. The SVO controller demonstrated significant improvement over the present arm performance: (1) Damping level was improved by a factor of 3; and (2) Peak joint torque was reduced by a factor of 2 following Shuttle thruster firings.

Scott, Michael A.↗
NASA NTRS1993

Reduction of Model Complexity by Active Control

The mathematical models of many dynamic systems of interest in the aerospace industry are inherently complex and of high order. Rather than grapple with the full-complexity models for such systems, the control designers often elect to derive low-order, reduced-complexity models for which a control system can be designed. The subject of model-order reduction has received a significant amount of attention in control engineering literature. This paper describes and demonstrates a novel active-control methodology that can be used to design a control system that automatically forces the original system to behave like a chosen reduced-complexity model by treating the effects of the original complexity-related terms as disturbances acting on the reduced-complexity system. The method is demonstrated by several worked examples involving both linear and nonlinear systems, supported by simulation results.

Bukley, Angelia P.↗
NASA NTRS1989

Numerical studies of identification in nonlinear distributed parameter systems

An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

Banks, H. T.↗
NASA NTRS1994

Pulsed acceleration in solar flares

We study the nonlinear dynamics of particle acceleration in solar flares by analyzing the time series of various quasi-periodic radio signatures during flares. In particular we present the radio and hard X-ray data of three flares which suppport the following tentative conclusions: (1) Particle acceleration and injection into magnetic structures occurs intrinsically in a pulsed mode (with a typical period of 1-2 s), produced by a single, spatially coherent, nonlinear system, rather than by a stochastic system with many spatially independent components ('statistical flare' produced by a fragmented primary energy release). (2) The nonlinear (quasi-periodic) mode of pulsed particle acceleration and injection into a coronal loop can be stabilized by phase locking with an MHD wave (oscillation) mode, if both periods are close to each other. (3) Pulsed injection of electron beams into a coronal loop may trigger nonlinear relaxational oscillations of wave-particle interactions. This is particularly likely when the limit cycles of both systems are similar.

Aschwanden, Markus J.↗
NASA NTRS2011

LaPlace Transform1 Adaptive Control Law in Support of Large Flight Envelope Modeling Work

This paper presents results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are in support of nonlinear aerodynamic modeling and instrumentation calibration.

Gregory, Irene M.↗
NASA NTRS1976

Digital signal processing and control and estimation theory -- Points of tangency, area of intersection, and parallel directions

A number of current research directions in the fields of digital signal processing and modern control and estimation theory were studied. Topics such as stability theory, linear prediction and parameter identification, system analysis and implementation, two-dimensional filtering, decentralized control and estimation, image processing, and nonlinear system theory were examined in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the two disciplines. An extensive bibliography is included.

Willsky, A. S.↗
NASA NTRS1987

Lyapunov exponents for infinite dimensional dynamical systems

Classically it was held that solutions to deterministic partial differential equations (i.e., ones with smooth coefficients and boundary data) could become random only through one mechanism, namely by the activation of more and more of the infinite number of degrees of freedom that are available to such a system. It is only recently that researchers have come to suspect that many infinite dimensional nonlinear systems may in fact possess finite dimensional chaotic attractors. Lyapunov exponents provide a tool for probing the nature of these attractors. This paper examines how these exponents might be measured for infinite dimensional systems.

Mhuiris, Nessan Mac Giolla↗
NASA NTRS1990

Improved operation of magnetic bearings for flywheel energy storage system

Analysis and operation of prototype 500-Wh flywheel at low speeds have shown that many factors affect the correct functioning of the magnetic bearings. An examination is made of a number of these, including magnetic bearing control system nonlinearities and displacement transducer positioning, and their effects upon the successful operation of the suspension system. It is observed that the bearing control system is extremely sensitive to actuator parameters such as coil inductance. As a consequence of the analysis of bearing relaxation oscillations, the bearing actuator design methodology which has previously been used, where coil parameter selection is based upon static considerations, has been revised. Displacement transducer sensors which overcome the collocation problem are discussed.

Zmood, R. B.↗
NASA NTRS2001

Applications of the Hilbert-Huang Transform

A new method, the Hilbert-Huang Transform, has been developed for analyzing nonlinear and nonstationary data. The key part of the method is the Empirical Mode Decomposition with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An M is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies'as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. With this technique we can examine the detailed dynamics characteristics of a nonlinear system through the instantaneous frequency rather than harmonics. Thus it constitutes a new view of the nonlinear dynamics. Examples of classic nonlinear equations and other nonlinear and nonstationary data sets will be used as examples to illustrate the advantage of the application of this new data analysis method.

Huang, Norden E.↗