Generalized superposition.
Generalization of superposition principle for linear systems applied to classification of nonlinear systems and solution of nonlinear filtering problems
Oppenheim, A. V.↗
SEARCH · Engineering Papers
Results for “nonlinear filtering”
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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Suboptimal state estimation for continuous-time nonlinear systems from discrete noisy measurements.
Continuous time nonlinear dynamical system states variables estimated suboptimally from discrete noisy measurements with second order nonlinear filter, deriving dynamical equations
Athans, M.↗
Suboptimal state estimation for continuous-time nonlinear systems from discrete noisy measurements.
Continuous time nonlinear dynamical system states variables estimated suboptimally from discrete noisy measurements with second order nonlinear filter, deriving dynamical equations
Athans, M.↗
Atmospheric re-entry into the Martian atmosphere with variable lift control
Space capsule reentry into Martian atmosphere for soft landing, using onboard nonlinear filter and stochastic control for random wind gusts
Ohtakay, H.↗
Adaptive control of stochastic linear systems with unknown parameters
The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.
Ku, R. T.↗
Nonlinear estimation theory applied to orbit determination
The development of an approximate nonlinear filter using the Martingale theory and appropriate smoothing properties is considered. Both the first order and the second order moments were estimated. The filter developed can be classified as a modified Gaussian second order filter. Its performance was evaluated in a simulated study of the problem of estimating the state of an interplanetary space vehicle during both a simulated Jupiter flyby and a simulated Jupiter orbiter mission. In addition to the modified Gaussian second order filter, the modified truncated second order filter was also evaluated in the simulated study. Results obtained with each of these filters were compared with numerical results obtained with the extended Kalman filter and the performance of each filter is determined by comparison with the actual estimation errors. The simulations were designed to determine the effects of the second order terms in the dynamic state relations, the observation state relations, and the Kalman gain compensation term. It is shown that the Kalman gain-compensated filter which includes only the Kalman gain compensation term is superior to all of the other filters.
Choe, C. Y.↗
Nonlinear and adaptive estimation in reentry.
The problem of real-time estimation of a lifting reentry vehicle trajectory of the shuttle orbiter type is considered. Simulations feature large position and velocity uncertainties at radar acquisition and realistic model errors in lift, drag and other model parameters. Radar tracking and accelerometer data are simulated. Significant nonlinearities are found to exist on spacecraft acquisition. An iterated nonlinear filter is shown to perform optimally during the radar acquisition phase. An adaptive filter is shown to track time-varying model errors, such as errors in the lift and drag coefficients, down to the noise level. Such real-time model tracking (identification) is frequently required for guidance and control implementation.
Jazwinski, A. H.↗
Coordinated adaptive washout for motion simulators.
This paper introduces a new method of providing motion cues to a moving base six-degree-of-freedom flight simulator utilizing nonlinear filters. Coordinated adaptive filters, used to coordinate translational and rotational motion, are derived based on the method of continuous steepest descent, and the basic concept of the digital controllers used for the uncoordinated heave and yaw cues is also presented. The coordinated adaptive washout method is illustrated by an application in a six-degree-of-freedom fixed-base environment.
Parrish, R. V.↗
Empirical comparison of a linear and a nonlinear washout for motion simulators
The subjective opinions gathered from seven pilots in the process of comparing a linear and a nonlinear washout for motion simulators reveal an important advance in motion cue presentation. The advance is not in the increased cue provided by the nonlinear filter over a linear filter for the same amount of motion base travel, but rather in the elimination of false rotational rate cues presented by linear filters.
Parrish, R. V.↗
Control optimization, stabilization and computer algorithms for aircraft applications
Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.
Source record↗
Design and simulation of stratified probability digital receiver with application to the multipath communication
One approach to the problem of simplifying complex nonlinear filtering algorithms is through using stratified probability approximations where the continuous probability density functions of certain random variables are represented by discrete mass approximations. This technique is developed in this paper and used to simplify the filtering algorithms developed for the optimum receiver for signals corrupted by both additive and multiplicative noise.
Deal, J. H.↗
Parameter adaptive estimation of random processes
This paper is concerned with the parameter adaptive least squares estimation of random processes. The main result is a general representation theorem for the conditional expectation of a random variable on a product probability space. Using this theorem along with the general likelihood ratio expression, the least squares estimate of the process is found in terms of the parameter conditioned estimates. The stochastic differential for the a posteriori probability and the stochastic differential equation for the a posteriori density are found by using simple stochastic calculus on the representations obtained. The results are specialized to the case when the parameter has a discrete distribution. The results can be used to construct an implementable recursive estimator for certain types of nonlinear filtering problems. This is illustrated by some simple examples.
Caglayan, A. K.↗
Simulated performance of the NASA 30/20 GHz test transponder using multi-H phase coded modulation
The performance of a proposed NASA 30/20 GHz satellite communications system is studied for multi-h phase coded modulation (MHPM) schemes. The techniques used to model and simulate a satellite communications channel including transmitter, receiver, filters, nonlinearities, and interferers are presented. The performance of various MHPM schemes is compared for several different channel configurations. As a measure of performance, the probability of bit error vs Eb/NO is computed using a Monte Carlo simulation technique. It is found that, regardless of the channel configuration, MHPM schemes can provide power efficiency over serial minimum shift keying modulation.
Meader, C. B.↗
In flight demonstration of mass property identification and jet plume interaction on the AeroAssist Flight Experiment
Algorithms have been developed for in-flight demonstration of spacecraft mass, center of mass, and inertia matrix which autonomously measure mass properties as they change in-flight due to consumable expenditures, payload deployment/retrieval, and docking. The testing of these algorithms can be conducted by means of a mass-properties estimator, which is a second-order nonlinear filter resembling an extended Kalman filter. The AeroAssist Flight Experiment, which will demonstrate the use of the earth's atmosphere to assist orbital changes, will carry the Rarefied-flow Aerodynamic Measurement Experiment (RAME); data taken by RAME will be used by the mass-properties estimator to ascertain spacecraft mass properties, and estimates from this filter will be compared to predicted values of the mass properties to validate the estimator.
Bergmann, Edward V.↗
Treating convection in sequential solvers
The treatment of the convection terms in the sequential solver, a standard procedure found in virtually all pressure based algorithms, to compute the flow problems with sharp gradients and source terms is investigated. Both scalar model problems and one-dimensional gas dynamics equations have been used to study the various issues involved. Different approaches including the use of nonlinear filtering techniques and adoption of TVD type schemes have been investigated. Special treatments of the source terms such as pressure gradients and heat release have also been devised, yielding insight and improved accuracy of the numerical procedure adopted.
Shyy, Wei↗
Information processing in the primate visual system - An integrated systems perspective
The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.
Van Essen, David C.↗
Heat Pipe Vapor Dynamics
The dynamic behavior of the vapor flow in heat pipes is investigated at startup and during operational transients. The vapor is modeled as two-dimensional, compressible viscous flow in an enclosure with inflow and outflow boundary conditions. For steady-state and operating transients, the SIMPLER method is used. In this method a control volume approach is employed on a staggered grid which makes the scheme very stable. It is shown that for relatively low input heat fluxes the compressibility of the vapor flow is low and the SIMPLER scheme is suitable for the study of transient vapor dynamics. When the input heat flux is high or the process under a startup operation starts at very low pressures and temperatures, the vapor is highly compressible and a shock wave is created in the evaporator. It is shown that for a wide range of input heat fluxes, the standard methods, including the SIMPLER scheme, are not suitable. A nonlinear filtering technique, along with the centered difference scheme, are then used for shock capturing as well as for the solution of the cell Reynolds-number problem. For high heat flux, the startup transient phase involves multiple shock reflections in the evaporator region. Each shock reflection causes a significant increase in the local pressure and a large pressure drop along the heat pipe. Furthermore, shock reflections cause flow reversal in the evaporation region and flow circulations in the adiabatic region. The maximum and maximum-averaged pressure drops in different sections of the heat pipe oscillate periodically with time because of multiple shock reflections. The pressure drop converges to a constant value at steady state. However, it is significantly higher than its steady-state value at the initiation of the startup transient. The time for the vapor core to reach steady-state condition depends on the input heat flux, the heat pipe geometry, the working fluid, and the condenser conditions. However, the vapor transient time, for an Na-filled heat pipe is on the order of seconds. Depending on the time constant for the overall system, the vapor transient time may be very short. Therefore, the vapor core may be assumed to be quasi-steady in the transient analysis of a heat pipe operation.
Issacci, Farrokh↗
Neural networks: Application to medical imaging
The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.
Clarke, Laurence P.↗