ALBERT

Description: A guidance and control method was developed to detect and exploit thermals for energy gain. Latency in energy rate estimation degraded performance. The concept of a UAV harvesting energy from the atmosphere has been shown to be feasible with existing technology. Many UAVs have similar mission constraints to birds and sailplanes. a) Surveillance; b) Point to point flight with minimal energy; and c) Increased ground speed.

Description: The primary objective of the UAVSAR Project is to develop a miniaturized polarimetric L-band synthetic aperture radar (SAR) for use on an unmanned aerial vehicle (UAV) or minimally piloted vehicle. This viewgraph presentation reviews NASA Dryden's role in the UAVSAR program. The G-III aircraft is described and shown, as well as a high level system architecture. The goals of the Platform Precision Autopilot (PPA) that it are shall fly the G-III within a 10 m (32.8 ft) diameter tube for at least 90% of each data take in conditions of calm to light atmospheric disturbances, as defined in MIL-STD-1797. That it minimize motion during data collection. It is critical to operate the UAVSAR System on a steady platform.

Description: This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.

Description: A guidance and control method was developed to detect and exploit thermals for energy gain. Latency in energy rate estimation degraded performance. The concept of a UAV harvesting energy from the atmosphere has been shown to be feasible with existing technology. Many UAVs have similar mission constraints to birds and sailplanes. a) Surveillance; b) Point to point flight with minimal energy; and c) Increased ground speed.

Description: A viewgraph presentation on autonomous soaring flight results for Unmanned Aerial Vehicles (UAV)'s is shown. The topics include: 1) Background; 2) Thermal Soaring Flight Results; 3) Autonomous Dolphin Soaring; and 4) Future Plans.

Description: This year, an improved adaptive-feedback control method was demonstrated that suppresses thermoacoustic instabilities in a liquid-fueled combustor of a type used in aircraft engines. Extensive research has been done to develop lean-burning (low fuel-to-air ratio) combustors that can reduce emissions throughout the mission cycle to reduce the environmental impact of aerospace propulsion systems. However, these lean-burning combustors are susceptible to thermoacoustic instabilities (high-frequency pressure waves), which can fatigue combustor components and even downstream turbine blades. This can significantly decrease the safe operating life of the combustor and turbine. Thus, suppressing the thermoacoustic combustor instabilities is an enabling technology for meeting the low-emission goals of the NASA Ultra-Efficient Engine Technology (UEET) Project.

Description: In an effort to expand pilot training methods to avoid icing-related accidents, the NASA Glenn Research Center and Bihrle Applied Research Inc. have developed the Ice Contamination Effects Flight Training Device (ICEFTD). ICEFTD simulates the flight characteristics of the NASA Twin Otter Icing Research Aircraft in a no-ice baseline and in two ice configurations simulating ice-protection-system failures. Key features of the training device are the force feedback in the yoke, the instrument panel and out-the-window graphics, the instructor s workstation, and the portability of the unit.

Description: A flight investigation was made at altitudes of 40,000, 25,000 and 15,000 feet to determine the horizontal-tail loads of the Bell X-5 research airplane at a sweep angle of 58.7 deg over the lift range of the airplane for Mach numbers from 0.61 to 1.00. The horizontal-tail loads were found to be nonlinear with lift throughout the lift ranges tested at all Mach numbers except at a Mach number of 1.00. The balancing tail loads reflected the changes which occur in the wing characteristics with increasing angle of attack. The nonlinearities were, in general, more pronounced at the higher angles of attack near the pitch-up where the balancing tail loads indicate that the wing-fuselage combination becomes unstable. No apparent effects of altitude on the balancing tail loads were evident over the comparable lift ranges of these tests at altitudes from 40,000 feet to 15,000 feet. Comparisons of balancing tail loads obtained from flight and windtunnel tests indicated discrepancies in absolute magnitudes, but the general trends of the data agree. Some differences in absolute magnitude may be accounted for by the tail load carried inboard of the strain-gage station and the load induced on the fuselage by the presence of the tail. These loads were not measured in flight.

Description: In-flight sensor fault detection and isolation (FDI) is critical to maintaining reliable engine operation during flight. The aircraft engine control system, which computes control commands on the basis of sensor measurements, operates the propulsion systems at the demanded conditions. Any undetected sensor faults, therefore, may cause the control system to drive the engine into an undesirable operating condition. It is critical to detect and isolate failed sensors as soon as possible so that such scenarios can be avoided. A challenging issue in developing reliable sensor FDI systems is to make them robust to changes in engine operating characteristics due to degradation with usage and other faults that can occur during flight. A sensor FDI system that cannot appropriately account for such scenarios may result in false alarms, missed detections, or misclassifications when such faults do occur. To address this issue, an enhanced bank of Kalman filters was developed, and its performance and robustness were demonstrated in a simulation environment. The bank of filters is composed of m + 1 Kalman filters, where m is the number of sensors being used by the control system and, thus, in need of monitoring. Each Kalman filter is designed on the basis of a unique fault hypothesis so that it will be able to maintain its performance if a particular fault scenario, hypothesized by that particular filter, takes place.

Description: The Tropical Rainfall Measuring Mission (TRMM) spacecraft, a joint mission between the U.S. and Japan, launched onboard an HI1 rocket on November 27,1997 and transitioned in August, 2001 from an average operating altitude of 350 kilometers to 402.5 kilometers. Due to problems using the Earth Sensor Assembly (ESA) at the higher altitude, TRMM switched to a backup attitude control mode. Prior to the orbit boost TRMM controlled pitch and roll to the local vertical using ESA measurements while using gyro data to propagate yaw attitude between yaw updates from the Sun sensors. After the orbit boost, a Kalman filter used 3-axis gyro data with Sun sensor and magnetometers to estimate onboard attitude. While originally intended to meet a degraded attitude accuracy of 0.7 degrees, the new control mode met the original 0.2 degree attitude accuracy requirement after improving onboard ephemeris prediction and adjusting the magnetometer calibration onboard. Independent roll attitude checks using a science instrument, the Precipitation Radar (PR) which was built in Japan, provided a novel insight into the pointing performance. The PR data helped identify the pointing errors after the orbit boost, track the performance improvements, and show subtle effects from ephemeris errors and gyro bias errors. It also helped identify average bias trends throughout the mission. Roll errors tracked by the PR from sample orbits pre-boost and post-boost are shown in Figure 1. Prior to the orbit boost the largest attitude errors were due to occasional interference in the ESA. These errors were sometime larger than 0.2 degrees in pitch and roll, but usually less, as estimated from a comprehensive review of the attitude excursions using gyro data. Sudden jumps in the onboard roll show up as spikes in the reported attitude since the control responds within tens of seconds to null the pointing error. The PR estimated roll tracks well with an estimate of the roll history propagated using gyro data. After the orbit boost, the attitude errors shown by the PR roll have a smooth sine-wave type signal because of the way that attitude errors propagate with the use of gyro data. Yaw errors couple at orbit period to roll with '/4 orbit lag. By tracking the amplitude, phase, and bias of the sinusoidal PR roll error signal, it was shown that the average pitch rotation axis tends to be offset from orbit normal in a direction perpendicular to the Sun direction, as shown in Figure 2 for a 200 day period following the orbit boost. This is a result of the higher accuracy and stability of the Sun sensor measurements relative to the magnetometer measurements used in the Kalman filter. In November, 2001 a magnetometer calibration adjustment was uploaded which improved the pointing performance, keeping the roll and yaw amplitudes within about 0.1 degrees. After the boost, onboard ephemeris errors had a direct effect on the pitch pointing, being used to compute the Earth pointing reference frame. Improvements after the orbit boost have kept the the onboard ephemeris errors generally below 20 kilometers. Ephemeris errors have secondary effects on roll and yaw, especially during high beta angle when pitch effects can couple into roll and yaw. This is illustrated in figure 3. The onboard roll bias trends as measured by PR data show correlations with the Kalman filter's gyro bias error. This particularly shows up after yaw turns (every 2 to 4 weeks) as shown in Figure 3, when a slight roll bias is observed while the onboard computed gyro biases settle to new values. As for longer term trends, the PR data shows that the roll bias was influenced by Earth horizon radiance effects prior to the boost, changing values at yaw turns, and indicated a long term drift as shown in Figure 4. After the boost, the bias variations were smaller and showed some possible correlation with solar beta angle, probably due to sun sensor misalignment effects.