Detecting False Data Injection Attacks to Battery State Estimation Using Cumulative Sum Algorithm.
Abstract not provided.
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.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Abstract not provided.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Space shuttle position and velocity estimates for approach, using inertial subsystem and scanning beam microwave ILS receiver
Explore the source record for details and available documents.
The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.
A computational algorithm for the identification of biases in discrete-time, nonlinear, stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.
A computational algorithm for the identification of input and output biases in discrete-time nonlinear stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.
Explore the source record for details and available documents.
One of the major concerns in the design of an active control system is obtaining the information needed for effective feedback. This involves the combination of sensing and estimation. A sensor location index is defined as the weighted sum of the mean square estimation errors in which the sensor locations can be regarded as estimator design parameters. The design goal is to choose these locations to minimize the sensor location index. The choice of the number of sensors is a tradeoff between the estimation quality based upon the same performance index and the total costs of installing and maintaining extra sensors. An experimental study for choosing the sensor location was conducted on an aeroelastic system. The system modeling which includes the unsteady aerodynamics model developed by Stephen Rock was improved. Experimental results verify the trend of the theoretical predictions of the sensor location index for different sensor locations at various wind speeds.
Control effectiveness tests of reaction wheel actuators on a highly flexible grid are reported herein. Analytic determination of actuator control effectiveness is accomplished with finite element modelling. Experimental determination is done with two algorithms. The first is an equation error parameter identification scheme which estimates the control coefficients of the second order difference equation model of each vibration mode. The second is a least square error algorithm using the same model. For both methods there is a lack of agreement with analytic prediction.
Explore the source record for details and available documents.