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Rizvi, Farheen

Publications and source records attributed to Rizvi, Farheen.

8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

NISAR Spacecraft Environmental Torque Modeling During Operations

Environmental torques imparted on the NISAR (NASA-ISRO (NASA Jet PropulsionLaboratory (JPL)-Indian Space Research Organization (ISRO) Synthetic Aperture Radar) spacecraft are modeled. The environmental torques comprise of the gravity gradient, atmospheric drag, and solar radiation pressure. These torques act as external disturbances on the spacecraft and cause momentum to accumulate. This momentum needs to be unloaded via attitude control hardware. In order to size the hardware, it is important to determine the environmental torques imparted on the spacecraft. The results indicate that the worst case gravity gradient, drag, and solar radiation pressure torques are 7.4 by 10 (sup -3) Nm (Newton meters), 6.01 by 10 (sup -3) Nm, and 14.03 by 10(sup -3) Nm, respectively.

Rizvi, Farheen↗
NASA NTRS2016

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Soil Moisture Active Passive↗
NASA NTRS2013

Reducing Earth Topography Resolution for SMAP Mission Ground Tracks Using K-Means Clustering

The K-means clustering algorithm is used to reduce Earth topography resolution for the SMAP mission ground tracks. As SMAP propagates in orbit, knowledge of the radar antenna footprints on Earth is required for the antenna misalignment calibration. Each antenna footprint contains a latitude and longitude location pair on the Earth surface. There are 400 pairs in one data set for the calibration model. It is computationally expensive to calculate corresponding Earth elevation for these data pairs. Thus, the antenna footprint resolution is reduced. Similar topographical data pairs are grouped together with the K-means clustering algorithm. The resolution is reduced to the mean of each topographical cluster called the cluster centroid. The corresponding Earth elevation for each cluster centroid is assigned to the entire group. Results show that 400 data points are reduced to 60 while still maintaining algorithm performance and computational efficiency. In this work, sensitivity analysis is also performed to show a trade-off between algorithm performance versus computational efficiency as the number of cluster centroids and algorithm iterations are increased.

ground tracks↗
NASA NTRS2013

Reducing Pointing Errors During Cassini Reaction Control System Orbit Trim Maneuvers

The effect of altering a gain parameter in the Cassini reaction control system (RCS) delta-V controller on the maneuver execution errors during orbit trim maneuvers (OTMs) is explored. Cassini consists of two reaction control thruster branches (A & B) each with eight thrusters. Currently, the B-branch is operational while the A-branch serves as a back-up. The four Z-thrusters control the X and Y-axes, while the four Y-thrusters control the Z-axis. During an OTM, the Z-thrusters fire to maintain the X and Y-axes pointing within an attitude control dead-zone (-10 to 10 milliradians). The errors do not remain at zero due to pointing error sources such as spacecraft center of mass offset from the geometric center of the Z-facing thrusters, and variability in the thruster forces due to the thruster hardware differences. The delta-V reaction control system (RCS) controller ensures that the attitude error remains within this dead-zone. Gain parameters within the RCS delta-V controller affect the maneuver execution errors. Different parameter values are used to explore effect on these errors. It is found that pointing error decreases and magnitude error increases rapidly for gain parameters 10 times greater than the current parameter values used in the flight software.

European Space Agency (ESA)↗
NASA NTRS2013

Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft

A report describes a model that estimates the orientation of the backup reaction wheel using the reaction wheel spin rates telemetry from a spacecraft. Attitude control via the reaction wheel assembly (RWA) onboard a spacecraft uses three reaction wheels (one wheel per axis) and a backup to accommodate any wheel degradation throughout the course of the mission. The spacecraft dynamics prediction depends upon the correct knowledge of the reaction wheel orientations. Thus, it is vital to determine the actual orientation of the reaction wheels such that the correct spacecraft dynamics can be predicted. The conservation of angular momentum is used to estimate the orientation of the backup reaction wheel from the prime and backup reaction wheel spin rates data. The method is applied in estimating the orientation of the backup wheel onboard the Cassini spacecraft. The flight telemetry from the March 2011 prime and backup RWA swap activity on Cassini is used to obtain the best estimate for the backup reaction wheel orientation.

Rizvi, Farheen↗
NASA NTRS2012

Cassini Thruster Calibration Algorithm Using Reaction Wheel Biasing Data

Thrust force estimates for the reaction control thrusters on-board Cassini spacecraft are presented in this paper. Cassini consists of two thruster branches (A and B) each with eight thrusters. The four Z-thrusters control the X and Y-axes, while the four Y-thrusters control the Z-axis. It is important to track the thrust force estimates in order to detect any thruster degradation and for supporting various activities in spacecraft operations (Titan flyby, spacecraft maneuvers). The Euler equation, which describes the rotational motion of the spacecraft during a reaction wheel bias event, is used to develop the algorithm. The thrust estimates are obtained from the pseudo inverse solution using flight telemetry during the bias. Results show that the A-branch Z3A and Z4A thrusters exhibited degraded thrust in November 2008. Due to the degraded thrust performance of Z3A and Z4A, A-branch usage was discontinued and prime branch was swapped to B-branch in March 2009. The thrust estimates from the B-branch do not show any degradation to date. The algorithm is used to trend the B-branch thrust force estimates as the mission continues.

attitude control↗
NASA NTRS2011

Characterizing Observed Limit Cycles in the Cassini Main Engine Guidance Control System

The Cassini spacecraft dynamics-related telemetry during long Main Engine (ME) burns has indicated the presence of stable limit cycles between 0.03-0.04 Hz frequencies. These stable limit cycles cause the spacecraft to possess non-zero oscillating rates for extended periods of time. This indicates that the linear ME guidance control system does not model the complete dynamics of the spacecraft. In this study, we propose that the observed limit cycles in the spacecraft dynamics telemetry appear from a stable interaction between the unmodeled nonlinear elements in the ME guidance control system. Many nonlinearities in the control system emerge from translating the linear engine gimbal actuator (EGA) motion into a spacecraft rotation. One such nonlinearity comes from the gear backlash in the EGA system, which is the focus of this paper. The limit cycle characteristics and behavior can be predicted by modeling this gear backlash nonlinear element via a describing function and studying the interaction of this describing function with the overall dynamics of the spacecraft. The linear ME guidance controller and gear backlash nonlinearity are modeled analytically. The frequency, magnitude, and nature of the limit cycle are obtained from the frequency response of the ME guidance controller and nonlinear element. In addition, the ME guidance controller along with the nonlinearity is simulated. The simulation response contains a limit cycle with similar characterstics as predicted analytically: 0.03-0.04 Hz frequency and stable, sustained oscillations. The analytical and simulated limit cycle responses are compared to the flight telemetry for long burns such as the Saturn Orbit Insertion and Main Engine Orbit Trim Maneuvers. The analytical and simulated limit cycle characteristics compare well with the actual observed limit cycles in the flight telemetry. Both have frequencies between 0.03-0.04 Hz and stable oscillations. This work shows that the stable limit cycles occur due to the interaction between the unmodeled nonlinear elements and linear ME guidance controller.

stable limit cycle↗