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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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NASA NTRS1990

System Identification for Nonlinear Control Using Neural Networks

An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.

Stengel, Robert F.↗
NASA NTRS1991

A system identification model for adaptive nonlinear control

A system identification model that combines generalized-spline function approximation with a nonlinear control system is described. The complete control system contains three main elements: a nonlinear-inverse-dynamic control law that depends on a comprehensive model of the plant, a state estimator whose outputs drive the control law, and a function approximation scheme that models the system dynamics. The system-identification task, which combines an extended Kalman filter with a function approximator modeled as an artificial neural network, is considered. The results of an application of the identification techniques to a nonlinear transport aircraft model are presented.

Linse, Dennis J.↗
NASA NTRS2021

Organized kinetic energy backscatter in the hurricane boundary layer from radar measurements

The fluid mechanics of hurricanes strongly depends on boundary layer energetics due to the warm-core nature of the system with peak velocities located at lower levels. One barrier that has inhibited a more complete characterization of energy transfer in the boundary layer is a lack of observations that resolve large, turbulent eddies. In particular, the occurrence and structure of upscale energy transfer (backscatter) in the hurricane boundary layer as well as the effects of backscatter on the vortex intensity are unknown. The analysis presented here of very high-resolution, three-dimensional wind observations from Hurricane Rita (2005) at peak intensity reveals large regions of organized backscatter in the boundary layer associated with coherent, turbulent eddies. Strong forwardscatter is also found next to the backscatter regions due to the interaction between adjacent eddies. Two components of the stress tensor are primarily responsible for this alternating scatter structure, as shown by large correlation coefficients between the fields: the radial–vertical component (τ13) and the azimuthal–vertical component (τ23) with average correlations of 79% and 49 %, respectively. The Leonard, Reynolds and cross-term stress components are also provided. The impact of the sub-filter-scale energy transfer is estimated by computing the kinetic energy budget for the resolved-scale and eddy-scale motions. The results show that the sub-filter-scale energy transfer term is of the same order as the other terms in the eddy-scale budgets, contributing between 16% and 40% to the local time tendency with an average contribution of approximately 30 %. These results indicate that the coherent turbulent eddies can affect the vortex dynamics through wave–wave nonlinear interactions, which can subsequently influence the wave–mean flow interactions. This is the first study to examine the full sub-filter-scale

Sydney Sroka↗
NASA NTRS1972

Stability analysis of Riccati covariance equations of Kalman filter.

The present paper takes the basic mathematical approach to analyze the stability of Riccati equations. First, a simple stability criterion like that of the linear constant coefficient system is sought for the nonlinear constant Riccati Equation. Then, a complete analysis on the limiting covariance P follows. The analysis is focussed on the main theorem. Finally, the computational aspects of the Riccati equations are analyzed with examples. The application of this analysis is to provide a simple stability criterion for the Kalman filter computation to test and predict filter convergence and thus modify filter parameters accordingly.

Teng, L.↗
NASA NTRS1982

Performance of staggered quadrature modulations over nonlinear satellite channels with uplink noise and intersymbol interference

In this paper, the performance of staggered quadrature modulations over nonlinear satellite channels is analyzed. The effects of uplink noise and intersymbol interference caused by transmitter filtering are included. The approach taken employs computational techniques based on moments of the interference. The expressions for the system bit error rate are derived for a general transponder model characterized by AM-AM and AM-PM conversion characteristics. Specific numerical results are presented for a hard-limited satellite repeater using staggered quadrature overlapped raised cosine (SQORC) and minimum-shift-keying (MSK) modulations.

Simon, M. K.↗
NASA NTRS1990

Optical calculation of correlation filters

A method is presented for designing optical correlation filters based on measuring intensity patterns in the Fourier plane. The method can be used in general to design any type of frequency plane filter but is especially attractive in the case of a binary phase only filter (BPOF). The method can produce a filter that is well matched to both the object, its transforming optical system and the spatial light modulator used in the correlator input plane. A working filter was produced using the technique, but the filter response was weak. The suspected causes of the weak output are imprecise Fourier plane positioning, nonlinearities in the recording process, and/or aliasing effects.

Knopp, Jerome↗
NASA NTRS1995

A Zonal Approach for Prediction of Jet Noise

A zonal approach for direct computation of sound generation and propagation from a supersonic jet is investigated. The present work splits the computational domain into a nonlinear, acoustic-source regime and a linear acoustic wave propagation regime. In the nonlinear regime, the unsteady flow is governed by the large-scale equations, which are the filtered compressible Navier-Stokes equations. In the linear acoustic regime, the sound wave propagation is described by the linearized Euler equations. Computational results are presented for a supersonic jet at M = 2. 1. It is demonstrated that no spurious modes are generated in the matching region and the computational expense is reduced substantially as opposed to fully large-scale simulation.

Shih, S. H.↗
NASA NTRS2000

Modeling the Dynamics of the Middle Atmosphere and Lower Thermosphere Under the Influence of Gravity Waves

Our Numerical Spectral Model (NSM), which extends from the ground up into the thermosphere, is non-linear, time-dependent and has been employed for 2D and 3D applications. The standard version of the NSM incorporates Hines' Doppler Spread Parameterization for small scale gravity waves (GW), but planetary waves generated in the troposphere have also been incorporated. The NSM has been applied to describe: (1) the anomalous seasonal variations of the zonal circulation and temperature in the upper mesosphere, (2) the equatorial oscillations (quasi-biennial and semi-annual oscillations (QBO and SAO)) extending from the stratosphere into the upper mesosphere, (3) the diurnal and semi-diurnal tides, and (4) the planetary waves that are excited in the mesosphere. With the emphasis to provide understanding, we present here results from numerical experiments with the NSM that shed light on the GW processes that are of central importance in the mesosphere and lower thermosphere. These are our conclusions: (1) The large semiannual variations in the diurnal tide (DT), with peak amplitudes observed around equinox, are produced primarily by GW interactions that involve, in part, planetary waves. The DT, like planetary waves, tends to be amplified by GW momentum deposition, which reduces also the vertical wavelength, but variations in eddy viscosity associated with GW interactions are also important. (2) The semidiurnal tide (SDT) and its phase in particular, is strongly influenced by the mean zonal circulation. The SDT, individually, is also amplified by GW. But the DT filters out GW such that the GW interaction effectively reduces the amplitude of the SDT, producing a strong nonlinear interaction between the DT and SDT. (3) Without external time dependent energy or momentum sources, planetary waves (PW) are generated in the model for zonal wavenumbers 1 to 4, which have amplitudes in the mesosphere above 50 km as large as 40 m/s and periods between 50 and 2 days. The waves are generated primarily during solstice conditions, which indicates that the baroclinic instability (associated with the GW induced reversal in the latitudinal temperature gradient) is playing an important role. Numerical experiment show that GW, directly, also greatly amplify the PW. A common feature of the PW generated in summer and winter is that their vertical wavelengths throughout the mesosphere are large, which indicates that the waves are not propagating freely but are generated throughout the region. Another common feature is that the PW propagate preferentially westward in summer and eastward in winter, being launched from the westward and eastward zonal winds that prevail respectively in summer and winter at altitudes below 80 km. (4) Planetary waves generated internally by baroclinic instability and GW interaction produce large amplitude modulations of the DT and SDT. In summary we conclude that GW play major roles in generating and amplifying the dynamical components in the MLT region and, acting principally through wave filtering, produce important non-linear interactions between the components.

Mayr, H. G.↗
NASA NTRS2011

Method and System for Temporal Filtering in Video Compression Systems

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Lu, Ligang↗
NASA NTRS1972

Encoding and decoding of color information using two-dimensional spatial filtering.

Spatial frequency encoding is described as it applies to both photographic and television systems. In each case, color separations amplitude modulate spatial frequency carriers. The photographic system separates the carriers in the two-dimensional Fourier transform plane using coherent optics; the television system employs a two-dimensional electrical filter to perform the same separation. These filters are synthesized so that the two-dimensional bandwidths of the television camera are used efficiently. Nonlinear processing techniques are also described to minimize crosstalk between channels.

Schaefer, L. F.↗
NASA NTRS1984

Normal Mode Initialization

The objective of this research is the development and implementation of normal mode procedures for use with the GLAS analysis/forecast system. Specific tasks of this work include: (1) high latitude filtering of model fields to preserve the GLAS GCM's linear stability during integration; (2) development of nonlinear normal mode initialization (NLNMI) processes, both adiabatic and diabatic. Using NLNMI to initialize GLAS analyses; investigation of the impact of normal mode initialization on the GLAS analysis/forecast system, especially in regard to data assimilation; and (3) diagnosis of the 1-3 day systemic forecast errors of the GLAS GCM.

Bloom, S. C.↗
NASA NTRS1999

Angular-Rate Estimation Using Delayed Quaternion Measurements

This paper presents algorithms for estimating the angular-rate vector of satellites using quaternion measurements. Two approaches are compared one that uses differentiated quaternion measurements to yield coarse rate measurements, which are then fed into two different estimators. In the other approach the raw quaternion measurements themselves are fed directly into the two estimators. The two estimators rely on the ability to decompose the non-linear part of the rotas rotational dynamics equation of a body into a product of an angular-rate dependent matrix and the angular-rate vector itself. This non unique decomposition, enables the treatment of the nonlinear spacecraft (SC) dynamics model as a linear one and, thus, the application of a PseudoLinear Kalman Filter (PSELIKA). It also enables the application of a special Kalman filter which is based on the use of the solution of the State Dependent Algebraic Riccati Equation (SDARE) in order to compute the gain matrix and thus eliminates the need to compute recursively the filter covariance matrix. The replacement of the rotational dynamics by a simple Markov model is also examined. In this paper special consideration is given to the problem of delayed quaternion measurements. Two solutions to this problem are suggested and tested. Real Rossi X-Ray Timing Explorer (RXTE) data is used to test these algorithms, and results are presented.

Azor, R.↗
NASA NTRS2000

Extended Decentralized Linear-Quadratic-Gaussian Control

A straightforward extension of a solution to the decentralized linear-Quadratic-Gaussian problem is proposed that allows its use for commonly encountered classes of problems that are currently solved with the extended Kalman filter. This extension allows the system to be partitioned in such a way as to exclude the nonlinearities from the essential algebraic relationships that allow the estimation and control to be optimally decentralized.

Carpenter, J. Russell↗
NASA NTRS1990

A simple dynamic engine model for use in a real-time aircraft simulation with thrust vectoring

A simple dynamic engine model was developed at the NASA Ames Research Center, Dryden Flight Research Facility, for use in thrust vectoring control law development and real-time aircraft simulation. The simple dynamic engine model of the F404-GE-400 engine (General Electric, Lynn, Massachusetts) operates within the aircraft simulator. It was developed using tabular data generated from a complete nonlinear dynamic engine model supplied by the manufacturer. Engine dynamics were simulated using a throttle rate limiter and low-pass filter. Included is a description of a method to account for axial thrust loss resulting from thrust vectoring. In addition, the development of the simple dynamic engine model and its incorporation into the F-18 high alpha research vehicle (HARV) thrust vectoring simulation. The simple dynamic engine model was evaluated at Mach 0.2, 35,000 ft altitude and at Mach 0.7, 35,000 ft altitude. The simple dynamic engine model is within 3 percent of the steady state response, and within 25 percent of the transient response of the complete nonlinear dynamic engine model.

Johnson, Steven A.↗
NASA NTRS1991

A simulation study of turbofan engine deterioration estimation using Kalman filtering techniques

Deterioration of engine components may cause off-normal engine operation. The result is an unecessary loss of performance, because the fixed schedules are designed to accommodate a wide range of engine health. These fixed control schedules may not be optimal for a deteriorated engine. This problem may be solved by including a measure of deterioration in determining the control variables. These engine deterioration parameters usually cannot be measured directly but can be estimated. A Kalman filter design is presented for estimating two performance parameters that account for engine deterioration: high and low pressure turbine delta efficiencies. The delta efficiency parameters model variations of the high and low pressure turbine efficiencies from nominal values. The filter has a design condition of Mach 0.90, 30,000 ft altitude, and 47 deg power level angle (PLA). It was evaluated using a nonlinear simulation of the F100 engine model derivative (EMD) engine, at the design Mach number and altitude over a PLA range of 43 to 55 deg. It was found that known high pressure turbine delta efficiencies of -2.5 percent and low pressure turbine delta efficiencies of -1.0 percent can be estimated with an accuracy of + or - 0.25 percent efficiency with a Kalman filter. If both the high and low pressure turbine are deteriorated, the delta efficiencies of -2.5 percent to both turbines can be estimated with the same accuracy.

Lambert, Heather H.↗
NASA NTRS1997

Crystalline Colloidal Arrays in Polymer Matrices

Crystalline Colloidal Arrays (CCA, also known as colloidal crystals), composed of aqueous or nonaqueous dispersions of self-assembled nanosized polymer colloidal spheres, are emerging toward the development of advanced optical devices for technological applications. The spontaneous self assembly of polymer spheres in a dielectric medium results from the electrostatic repulsive interaction between particles of uniform size and charge distribution. In a way similar to atomic crystals that diffract X-rays, CCA dispersions in thin quartz cells selectively and efficiently Bragg diffract the incident visible light. The reason for this diffraction is because the lattice (body or face centered cubic) spacing is on the order of the wavelength of visible light. Unlike the atomic crystals that diffract a fixed wavelength, colloidal crystals in principle, depending on the particle size, particle number and charge density, can diffract W, Vis or IR light. Therefore, the CCA dispersions can be used as laser filters. Besides, the diffraction intensity depends on the refractive index mismatch between polymer spheres and dielectric medium; therefore, it is possible to modulate incident light intensities by manipulating the index of either the spheres or the medium. Our interest in CCA is in the fabrication of all-optical devices such as optical switches, limiters, and spatial light modulators for optical signal processing. The two major requirements from a materials standpoint are the incorporation of suitable nonlinear optical materials (NLO) into polymer spheres which will allow us to alter the refractive index of the spheres by intense laser radiation, and preparation of solid CCA filters which can resist laser damage. The fabrication of solid composite filters not only has the advantage that the films are easier to handle, but also the arrays in solid films are more robust than in liquid media. In this paper, we report the photopolymerization process used to trap CCA in polymer matrices, the factors which affect the optical diffraction qualities of resulting polymer films, and methods to improve the efficiencies of solid optical filters. Before this, we also present the experimental demonstration, of controlling the optical diffraction intensities from aqueous CCA dispersions by varying the temperature, which establishes the feasibility of fabricating all-optical switching devices with nonlinear periodic array structures.

Sunkara, Hari B.↗
NASA NTRS1973

Model reference adaptive control using only input and output signals

It is shown how globally stable model reference adaptive control systems may be designed using only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Liapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Filtered derivatives of the plant output replace pure derivatives which are normally required in these systems. An augmented error signal replaces the error previously used which is the difference between the model and plant outputs. However, global stability is assured in the sense that this difference approaches zero asymptotically.

Monopoli, R. V.↗
NASA NTRS1990

Neuromorphic learning of continuous-valued mappings from noise-corrupted data. Application to real-time adaptive control

The ability of feed-forward neural network architectures to learn continuous valued mappings in the presence of noise was demonstrated in relation to parameter identification and real-time adaptive control applications. An error function was introduced to help optimize parameter values such as number of training iterations, observation time, sampling rate, and scaling of the control signal. The learning performance depended essentially on the degree of embodiment of the control law in the training data set and on the degree of uniformity of the probability distribution function of the data that are presented to the net during sequence. When a control law was corrupted by noise, the fluctuations of the training data biased the probability distribution function of the training data sequence. Only if the noise contamination is minimized and the degree of embodiment of the control law is maximized, can a neural net develop a good representation of the mapping and be used as a neurocontroller. A multilayer net was trained with back-error-propagation to control a cart-pole system for linear and nonlinear control laws in the presence of data processing noise and measurement noise. The neurocontroller exhibited noise-filtering properties and was found to operate more smoothly than the teacher in the presence of measurement noise.

Troudet, Terry↗