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  • 1
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    Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control (2003)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.
    Keywords: Aircraft Stability and Control
    Type: NASA/TM-2003-212028 , H-2543 , AIAA Paper 2003-5700 , AIAA Atmospheric Flight Mechanics Conference; Aug 11, 2003 - Aug 14, 2003; Austin, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 2
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    An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information (2013)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter. In order to increase overall robustness, the vehicle also has an alternate method of triggering the drogue parachute deployment based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this velocity-based trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers excellent performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.
    Keywords: Statistics and Probability
    Type: JSC-CN-27822 , AIAA GN and C Conference 2013; Aug 19, 2013 - Aug 22, 2013; Boston, MA; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 3
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    Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control (2003)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.
    Keywords: Aircraft Stability and Control
    Type: AIAA Paper 2003-5700 , AIAA Atmospheric Flight Mechanics Conference and Exhibit; Aug 11, 2003 - Aug 14, 2003; Austin, TX; United States
    Format: text
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    NASA TECHNICAL REPORTS
  • 4
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    Real-Time Stability Margin Measurements for X-38 Robustness Analysis (2005)
    In:  CASI
    Details
    Publication Date: 2019-07-11
    Description: A method has been developed for real-time stability margin measurement calculations. The method relies on a tailored-forced excitation targeted to a specific frequency range. Computation of the frequency response is matched to the specific frequencies contained in the excitation. A recursive Fourier transformation is used to make the method compatible with real-time calculation. The method was incorporated into the X-38 nonlinear simulation and applied to an X-38 robustness test. X-38 stability margins were calculated for different variations in aerodynamic and mass properties over the vehicle flight trajectory. The new method showed results comparable to more traditional stability analysis techniques, and at the same time, this new method provided coverage that is more complete and increased efficiency.
    Keywords: Aircraft Design, Testing and Performance
    Type: NASA/TP-2005-212856 , H-2565
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 5
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    Flight Test Results for the F-16XL With a Digital Flight Control System (2004)
    In:  CASI
    Details
    Publication Date: 2019-07-10
    Description: In the early 1980s, two F-16 airplanes were modified to extend the fuselage length and incorporate a large area delta wing planform. These two airplanes, designated the F-16XL, were designed by the General Dynamics Corporation (now Lockheed Martin Tactical Aircraft Systems) (Fort Worth, Texas) and were prototypes for a derivative fighter evaluation program conducted by the United States Air Force. Although the concept was never put into production, the F-16XL prototypes provided a unique planform for testing concepts in support of future high-speed supersonic transport aircraft. To extend the capabilities of this testbed vehicle the F-16XL ship 1 aircraft was upgraded with a digital flight control system. The added flexibility of a digital flight control system increases the versatility of this airplane as a testbed for aerodynamic research and investigation of advanced technologies. This report presents the handling qualities flight test results covering the envelope expansion of the F-16XL with the digital flight control system.
    Keywords: Aircraft Stability and Control
    Type: NASA/TP-2004-212046 , H-2554
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 6
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    Automated Re-Entry System using FNPEG (2017)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This paper discusses the implementation and simulated performance of the FNPEG (Fully Numerical Predictor-corrector Entry Guidance) algorithm into GNC FSW (Guidance, Navigation, and Control Flight Software) for use in an autonomous re-entry vehicle. A few modifications to FNPEG are discussed that result in computational savings -- a change to the state propagator, and a modification to cross-range lateral logic. Finally, some Monte Carlo results are presented using a representative vehicle in both a high-fidelity 6-DOF (degree-of-freedom) sim as well as in a 3-DOF sim for independent validation.
    Keywords: Aircraft Stability and Control
    Type: JSC-CN-38080 , AIAA SciTech Forum 2017; Jan 09, 2017 - Jan 13, 2017; Grapevine, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 7
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    A Rigid Mid-Lift-to-Drag Ratio Approach to Human Mars Entry, Descent, and Landing (2017)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Current NASA Human Mars architectures require delivery of approximately 20 metric tons of cargo to the surface in a single landing. A proposed vehicle type for performing the entry, descent, and landing at Mars associated with this architecture is a rigid, enclosed, elongated lifting body shape that provides a higher lift-to-drag ratio (L/D) than a typical entry capsule, but lower than a typical winged entry vehicle (such as the Space Shuttle Orbiter). A rigid Mid-L/D shape has advantages for large mass Mars EDL, including loads management, range capability during entry, and human spaceflight heritage. Previous large mass Mars studies have focused more on symmetric and/or circular cross-section Mid-L/D shapes such as the ellipsled. More recent work has shown performance advantages for non-circular cross section shapes. This paper will describe efforts to design a rigid Mid-L/D entry vehicle for Mars which shows mass and performance improvements over previous Mid-L/D studies. The proposed concept, work to date and evolution, forward path, and suggested future strategy are described.
    Keywords: Spacecraft Design, Testing and Performance
    Type: JSC-CN-37857 , AIAA SciTech 2017 Conference; Jan 09, 2017 - Jan 13, 2017; Grapevine, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 8
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    An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information (2013)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles
    Keywords: Launch Vehicles and Launch Operations
    Type: JSC-CN-29324 , American Institue of Aeronautics and Astronautics Guidance, Navigation, and Control (AIAA GN&C); Aug 19, 2013 - Aug 22, 2013; Boston, MA; United States
    Format: application/pdf
    Location Call Number Expected Availability
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    NASA TECHNICAL REPORTS
  • 9
    facet.materialart.
    Unknown
    An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information (2013)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.
    Keywords: Spacecraft Design, Testing and Performance
    Type: JSC-CN-29066 , AIAA Guidance, Navigation, and Control Conference; Aug 19, 2013 - Aug 22, 2013; Boston, MA; United States
    Format: application/pdf
    Location Call Number Expected Availability
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    NASA TECHNICAL REPORTS
  • 10
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    Orion Pad Abort 1 GN and C Design and Development (2010)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The first flight test of the Orion Abort Flight Test project is scheduled to launch in Spring 2010. This flight test is known as Pad Abort 1 (PA-1) and it is intended to accomplish a series of flight test objectives, including demonstrating the capability of the Launch Abort System (LAS) to propel the Crew Module (CM) to a safe distance from a launch vehicle during a pad abort. The PA-1 Flight Test Article (FTA) is actively controlled by a guidance, navigation, and control (GN&C) system for much of its flight. The purpose of this paper is to describe the design, development, and analysis of the PA-1 GN&C system. A description of the technical solutions that were developed to meet the challenge of satisfying many competing requirements is presented. A historical perspective of how the Orion LAV compares to the Apollo Launch Escape Vehicle (LEV) design will also be included.
    Keywords: Space Transportation and Safety
    Type: JSC-CN-19820 , AIAA Guidance Navigational Control Conference; Aug 02, 2010 - Aug 05, 2010; Toronto, Ontario; Canada
    Format: application/pdf
    Location Call Number Expected Availability
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    NASA TECHNICAL REPORTS
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