IRAC Full-scale Flight Test
This viewgraph presentation reviews Integrated Resilient Aircraft Control (IRAC) full scale flight tests.
Bosworth, John T.↗
Engineering topics
Bosworth, John T.
Publications and source records attributed to Bosworth, John T..
Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure
Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.
Bosworth, John T.↗
Full-Scale Flight Test
This viewgraph presentation reviews full-scale flight tests of the F/15 837 and F/A-18 853 aircrafts. A photograph of the C-17 T1 (USAF asset) is also provided.
Bosworth, John T.↗
Launch Abort System Flight Test Overview
This viewgraph presentation is an overview of the Launch Abort System (LAS) for the Constellation Program. The purpose of the paper is to review the planned tests for the LAS. The program will evaluate the performance of the crew escape functions of the Launch Abort System (LAS) specifically: the ability of the LAS to separate from the crew module, to gather flight test data for future design and implementation and to reduce system development risks.
Williams-Hayes, Peggy↗
Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure
Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.
Bosworth, John T.↗
F-15 837 IFCS Intelligent Flight Control System Project
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.
Bosworth, John T.↗
NASA Dryden Status
This viewgraph presentation reviews the recent activities of NASA Dryden Flight Research Center. Some of the activities are: the delivery of Ikhana, a platform to conduct Earth Science Missions; work on Autonomous Airborne Refueling Demonstration (AARD); progress in developing Quiet Spike, an extendable boom to reduce sonic boom signature; and work on Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Crew Exploration Vehicle (CEV)
Bosworth, John T.↗
Development and Flight Testing of a Neural Network Based Flight Control System on the NF-15B Aircraft
The Intelligent Flight Control System (IFCS) project at the NASA Dryden Flight Research Center, Edwards AFB, CA, has been investigating the use of neural network based adaptive control on a unique NF-15B test aircraft. The IFCS neural network is a software processor that stores measured aircraft response information to dynamically alter flight control gains. In 2006, the neural network was engaged and allowed to learn in real time to dynamically alter the aircraft handling qualities characteristics in the presence of actual aerodynamic failure conditions injected into the aircraft through the flight control system. The use of neural network and similar adaptive technologies in the design of highly fault and damage tolerant flight control systems shows promise in making future aircraft far more survivable than current technology allows. This paper will present the results of the IFCS flight test program conducted at the NASA Dryden Flight Research Center in 2006, with emphasis on challenges encountered and lessons learned.
Bomben, Craig R.↗
Real-Time Stability Margin Measurements for X-38 Robustness Analysis
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.
Bosworth, John T.↗
Flight Test Results for the F-16XL With a Digital Flight Control System
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.
Stachowiak, Susan J.↗
Flight Test of an Intelligent Flight-Control System
The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.
Davidson, Ron↗
Linearized Poststall Aerodynamic and Control Law Models of the X-31A Aircraft and Comparison with Flight Data
The X-31A aircraft has a unique configuration that uses thrust-vector vanes and aerodynamic control effectors to provide an operating envelope to a maximum 70 deg angle of attack, an inherently nonlinear portion of the flight envelope. This report presents linearized versions of the X-31A longitudinal and lateral-directional control systems, with aerodynamic models sufficient to evaluate characteristics in the poststall envelope at 30 deg, 45 deg, and 60 deg angle of attack. The models are presented with detail sufficient to allow the reader to reproduce the linear results or perform independent control studies. Comparisons between the responses of the linear models and flight data are presented in the time and frequency domains to demonstrate the strengths and weaknesses of the ability to predict high-angle-of-attack flight dynamics using linear models. The X-31A six-degree-of-freedom simulation contains a program that calculates linear perturbation models throughout the X-31A flight envelope. The models include aerodynamics and flight control system dynamics that are used for stability, controllability, and handling qualities analysis. The models presented in this report demonstrate the ability to provide reasonable linear representations in the poststall flight regime.
Stoliker, Patrick C.↗
Evaluation of High-Angle-of-Attack Handling Qualities for the X-31A Using Standard Evaluation Maneuvers
The X-31A aircraft gross-acquisition and fine-tracking handling qualities have been evaluated using standard evaluation maneuvers developed by Wright Laboratory, Wright Patterson Air Force Base. The emphasis of the testing is in the angle-of-attack range between 30 deg. and 70 deg. Longitudinal gross-acquisition handling qualities results show borderline Level l/Level 2 performance. Lateral gross-acquisition testing results in Level l/Level 2 ratings below 45 deg. angle of attack, degrading into Level 3 as angle of attack increases. The fine tracking performance in both longitudinal and lateral axes also receives Level 1 ratings near 30 deg. angle of attack, with the ratings tending towards Level 3 at angles of attack greater than 50 deg. These ratings do not match the expectations from the extensive close-in combat testing where the X-31A aircraft demonstrated fair to good handling qualities maneuvering for high angles of attack. This paper presents the results of the high-angle-of-attack handling qualities flight testing of the X-31A aircraft. Discussion of the preparation for the maneuvers, the pilot ratings, and selected pilot comments are included. Evaluation of the results is made in conjunction with existing Neal Smith, bandwidth, Smith-Geddes, and military specifications.
Stoliker, Patrick C.↗
Tailored Excitation for Multivariable Stability-Margin Measurement Applied to the X-31A Nonlinear Simulation
Safety and productivity of the initial flight test phase of a new vehicle have been enhanced by developing the ability to measure the stability margins of the combined control system and vehicle in flight. One shortcoming of performing this analysis is the long duration of the excitation signal required to provide results over a wide frequency range. For flight regimes such as high angle of attack or hypersonic flight, the ability to maintain flight condition for this time duration is difficult. Significantly reducing the required duration of the excitation input is possible by tailoring the input to excite only the frequency range where the lowest stability margin is expected. For a multiple-input/multiple-output system, the inputs can be simultaneously applied to the control effectors by creating each excitation input with a unique set of frequency components. Chirp-Z transformation algorithms can be used to match the analysis of the results to the specific frequencies used in the excitation input. This report discusses the application of a tailored excitation input to a high-fidelity X-31A linear model and nonlinear simulation. Depending on the frequency range, the results indicate the potential to significantly reduce the time required for stability measurement.
Bosworth, John T.↗
Evaluation of High-Angle-of-Attack Handling Qualities for the X-31A Using Standard Evaluation Maneuvers
The X-31A aircraft gross-acquisition and fine-tracking handling qualities have been evaluated using standard evaluation maneuvers developed by Wright Laboratory, Wright-Patterson Air Force Base. The emphasis of the testing is in the angle-of-attack range between 30 deg and 70 deg. Longitudinal gross-acquisition handling qualities results show borderline Level 1/Level 2 performance. Lateral gross-acquisition testing results in Level 1/Level 2 ratings below 45 deg angle of attack, degrading into Level 3 as angle of attack increases. The fine-tracking performance in both longitudinal and lateral axes also receives Level 1 ratings near 30 deg angle of attack, with the ratings tending towards Level 3 at angles of attack greater than 50 deg. These ratings do not match the expectations from the extensive close-in combat testing where the X-31A aircraft demonstrated fair to good handling qualities maneuvering for high angles of attack. This paper presents the results of the high-angle-of-attack handling qualities flight testing of the X-31A aircraft. Discussion of the preparation for the maneuvers, the pilot ratings, and selected pilot comments are included. Evaluation of the results is made in conjunction with existing Neal-Smith, bandwidth, Smith-Geddes, and military specifications.
Stoliker, Patrick C.↗
The X-31A quasi-tailless flight test results
A quasi-tailless flight investigation was launched using the X-31A enhanced fighter maneuverability airplane. In-flight simulations were used to assess the effect of partial to total vertical tail removal. The rudder control surface was used to cancel the stabilizing effects of the vertical tail, and yaw thrust vector commands were used to restabilize and control the airplane. The quasi-tailless mode was flown supersonically with gentle maneuvering and subsonically in precision approaches and ground attack profiles. Pilot ratings and a full set of flight test measurements were recorded. This report describes the results obtained and emphasizes the lessons learned from the X-31A flight test experiment. Sensor-related issues and their importance to a quasi-tailless simulation and to ultimately controlling a directionally unstable vehicle are assessed. The X-31A quasi-tailless flight test experiment showed that tailless and reduced tail fighter aircraft are definitely feasible. When the capability is designed into the airplane from the beginning, the benefits have the potential to outweigh the added complexity required.
Bosworth, John T.↗
X-29 flight control system: Lessons learned
Two X-29A aircraft were flown at the NASA Dryden Flight Research Center over a period of eight years. The airplanes' unique features are the forward-swept wing, variable incidence close-coupled canard and highly relaxed longitudinal static stability (up to 35-percent negative static margin at subsonic conditions). This paper describes the primary flight control system and significant modifications made to this system, flight test techniques used during envelope expansion, and results for the low- and high-angle-of-attack programs. Through out the paper, lessons learned will be discussed to illustrate the problems associated with the implementation of complex flight control systems.
Clarke, Robert↗
Linearized aerodynamic and control law models of the X-29A airplane and comparison with flight data
Flight control system design and analysis for aircraft rely on mathematical models of the vehicle dynamics. In addition to a six degree of freedom nonlinear simulation, the X-29A flight controls group developed a set of programs that calculate linear perturbation models throughout the X-29A flight envelope. The models include the aerodynamics as well as flight control system dynamics and were used for stability, controllability, and handling qualities analysis. These linear models were compared to flight test results to help provide a safe flight envelope expansion. A description is given of the linear models at three flight conditions and two flight control system modes. The models are presented with a level of detail that would allow the reader to reproduce the linear results if desired. Comparison between the response of the linear model and flight measured responses are presented to demonstrate the strengths and weaknesses of the linear models' ability to predict flight dynamics.
Bosworth, John T.↗