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Recent Experiences of the NASA Engineering and Safety Center (NESC) Guidance Navigation and Control (GN and C) Technical Discipline Team (TDT)

The NASA Engineering and Safety Center (NESC) is an independently funded NASA Program whose dedicated team of technical experts provides objective engineering and safety assessments of critical, high risk projects. NESC's strength is rooted in the diverse perspectives and broad knowledge base that add value to its products, affording customers a responsive, alternate path for assessing and preventing technical problems while protecting vital human and national resources. The Guidance Navigation and Control (GN&C) Technical Discipline Team (TDT) is one of fifteen such discipline-focused teams within the NESC organization. The TDT membership is composed of GN&C specialists from across NASA and its partner organizations in other government agencies, industry, national laboratories, and universities. This paper will briefly define the vision, mission, and purpose of the NESC organization. The role of the GN&C TDT will then be described in detail along with an overview of how this team operates and engages in its objective engineering and safety assessments of critical NASA.

Dennehy, Cornelius J.↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a streamlined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to pro-ceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule, development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor downselection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measurements for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jacob↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a stream-lined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to proceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule. Development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor down-selection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measure-ments for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jake↗

The Role of Guidance, Navigation, and Control in Hypersonic Vehicle Multidisciplinary Design and Optimization

Airbreathing hypersonic systems offer distinct performance advantages over rocket-based systems for space access vehicles. However, these performance advantages are dependent upon advances in current state-of-the-art technologies in many areas such as ram/scramjet propulsion integration, high temperature materials, aero-elastic structures, thermal protection systems, transition to hypersonics and hypersonic control elements within the framework of complex physics and new design methods. The complex interactions between elements of an airbreathing hypersonic vehicle represent a new paradigm in vehicle design to achieve the optimal performance necessary to meet space access mission objectives. In the past, guidance, navigation, and control (GNC) analysis often follows completion of the vehicle conceptual design process. Individual component groups design subsystems which are then integrated into a vehicle configuration. GNC is presented the task of developing control approaches to meet vehicle performance objectives given that configuration. This approach may be sufficient for vehicles where significant performance margins exist. However, for higher performance vehicles engaging the GNC discipline too late in the design cycle has been costly. For example, the X-29 experimental flight vehicle was built as a technology demonstrator. One of the many technologies to be demonstrated was the use of light-weight material composites for structural components. The use of light-weight materials increased the flexibility of the X- 29 beyond that of conventional metal alloy constructed aircraft. This effect was not considered when the vehicle control system was designed and built. The impact of this is that the control system did not have enough control authority to compensate for the effects of the first fundamental structural mode of the vehicle. As a result, the resulting pitch rate response of the vehicle was below specification and no post-design changes could recover the desired capability.

Ouzts, Peter J.↗

Guidance, navigation, and control subsystem equipment selection algorithm using expert system methods

Enhanced engineering tools can be obtained through the integration of expert system methodologies and existing design software. The application of these methodologies to the spacecraft design and cost model (SDCM) software provides an improved technique for the selection of hardware for unmanned spacecraft subsystem design. The knowledge engineering system (KES) expert system development tool was used to implement a smarter equipment section algorithm than that which is currently achievable through the use of a standard data base system. The guidance, navigation, and control subsystems of the SDCM software was chosen as the initial subsystem for implementation. The portions of the SDCM code which compute the selection criteria and constraints remain intact, and the expert system equipment selection algorithm is embedded within this existing code. The architecture of this new methodology is described and its implementation is reported. The project background and a brief overview of the expert system is described, and once the details of the design are characterized, an example of its implementation is demonstrated.

Allen, Cheryl L.↗

Guidance, Navigation, and Control Technology Assessment for Future Planetary Science Missions

Future planetary explorations envisioned by the National Research Council's (NRC's) report titled Vision and Voyages for Planetary Science in the Decade 2013-2022, developed for NASA Science Mission Directorate (SMD) Planetary Science Division (PSD), seek to reach targets of broad scientific interest across the solar system. This goal requires new capabilities such as innovative interplanetary trajectories, precision landing, operation in close proximity to targets, precision pointing, multiple collaborating spacecraft, multiple target tours, and advanced robotic surface exploration. Advancements in Guidance, Navigation, and Control (GN&C) and Mission Design in the areas of software, algorithm development and sensors will be necessary to accomplish these future missions. This paper summarizes the key GN&C and mission design capabilities and technologies needed for future missions pursuing SMD PSD's scientific goals.

position↗

Design, Development and Testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) Guidance, Navigation and Control System

Engineers at NASA Johnson Space Center have designed, developed, and tested a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spaceflight activities. The technology demonstration system, known as the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam), has been integrated into the approximate form and function of a flight system. The primary focus has been to develop a system capable of providing external views of the International Space Station. The Mini AERCam system is spherical-shaped and less than eight inches in diameter. It has a full suite of guidance, navigation, and control hardware and software, and is equipped with two digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations. Tests have been performed in both a six degree-of-freedom closed-loop orbital simulation and on an air-bearing table. The Mini AERCam system can also be used as a test platform for evaluating algorithms and relative navigation for autonomous proximity operations and docking around the Space Shuttle Orbiter or the ISS.

Wagenknecht, J.↗

Solar Dynamics Observatory Guidance, Navigation, and Control System Overview

The Solar Dynamics Observatory (SDO) was designed and built at the Goddard Space Flight Center, launched from Cape Canaveral on February 11, 2010, and reached its final geosynchronous science orbit on March 16, 2010. The purpose of SDO is to observe the Sun and continuously relay data to a dedicated ground station. SDO remains Sun-pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system (ACS) is a single-fault tolerant design. Its fully redundant attitude sensor complement includes sixteen coarse Sun sensors (CSSs), a digital Sun sensor (DSS), three two-axis inertial reference units (IRUs), and two star trackers (STs). The ACS also makes use of the four guide telescopes included as a part of one of the science instruments. Attitude actuation is performed using four reaction wheels assemblies (RWAs) and eight thrusters, with a single main engine used to provide velocity-change thrust for orbit raising. The attitude control software has five nominal control modes, three wheel-based modes and two thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. This paper details the final overall design of the SDO guidance, navigation, and control (GN&C) system and how it was used in practice during SDO launch, commissioning, and nominal operations. This overview will include the ACS control modes, attitude determination and sensor calibration, the high gain antenna (HGA) calibration, and jitter mitigation operation. The Solar Dynamics Observatory mission is part of the NASA Living With a Star program, which seeks to understand the changing Sun and its effects on the Solar System, life, and society. To this end, the SDO spacecraft carries three Sun-observing instruments: Helioseismic and Magnetic Imager (HMI), led by Stanford University; Atmospheric Imaging Assembly (AIA), led by Lockheed Martin Space and Astrophysics Laboratory; and Extreme Ultraviolet Variability Experiment (EVE), led by the University of Colorado. The basic mission is to observe the Sun for a very high percentage of the 5-year mission (10-year goal) with long stretches of uninterrupted observations and with constant, high-data-rate transmission to a dedicated ground station to be located in White Sands, New Mexico. These goals guided the design of the spacecraft bus that will carry and service the three-instrument payload. Overarching design goals for the bus are geosynchronous orbit, near-constant Sun observations with the ability to fly through eclipses, and constant HGA contact with the dedicated ground station. A three-axis stabilized ACS is needed both to point at the Sun accurately and to keep the roll about the Sun vector correctly positioned with respect to the solar north pole. This roll control is especially important for the magnetic field imaging of HM I. The mission requirements have several general impacts on the ACS design. Both the AIA and HMI instruments are very sensitive to the blurring caused by jitter. Each has an image stabilization system (ISS) with some ability to filter out high frequency motion, but below the bandwidth of the ISS the control system must compensate for disturbances within the ACS bandwidth or avoid exciting jitter at higher frequencies. Within the ACS bandwidth, the control requirement imposed by AIA is to place the center of the solar disk no more than 2 arc sec, 3 , from a body-defined target based on one of the GTs that accompany the instrument. This body-defined target, called the science reference boresight (SRB), was determined from the postlaunch orientation of the GTs by averaging the bounding telescope boresights for pitch to get a pitch SRB coordinate, and by averaging the bounding boresights for yaw toet the yaw SRB coordinate. The location of this SRB in the 0.5-deg field-of-view for each GT then becomes the central target for each telescope; one GT is selected for use as the ACS controlling guide telescope (CGT) at any given time. Fine Sun-pointing is effected based on this SRB for all three instruments when the Sun is within the linear range of the CGT. In addition to limiting jitter, HMI science requires averaging several observations, making the instrument sensitive to low frequency motion that induces differential motion between each observation. This requires the spacecraft attitude to be stable about the roll axis to approximately 10 arcsec over a ten-minute period. Instrument calibrations require that the spacecraft point the SRB up to 2.5 degrees in pitch and yaw away from the center of the Sun, placing the Sun outside the field-of-view of the guide telescopes. In such instances, when the GTs cannot provide the definitive target for the ACS, on-board attitude determination combined with ephemeris prediction of the Sun direction must provide the definitive target. EVE is capable of observing the Sun with less dependence on attitude control. However, the ground data processing needs for calibrations result in the most strict attitude knowledge requirements for the mission: [35,70,70] arcsec, 3 , of knowledge with respect to the center of the solar disk. In addition to driving the ACS sensor selection, the knowledge requirements, which have their effect primarily during Inertial mode calibrations, drive the accuracy requirements for the solar ephemeris. The need to achieve and maintain geosynchronous orbit (GEO) drove the need for high-efficiency propulsive systems and appropriate attitude control. The main engine provided high specific impulse for the maneuvers to attain GEO, while the smaller ACS thrusters managed the disturbance torques of the larger engine and provided the capability for much smaller adjustment burns on orbit. SDO s large solar profile means that solar radiation pressure is a large torque disturbance, and the momentum buildup from this disturbance and the GEO altitude drives the ACS to use thrusters to manage vehicle momentum. The demanding data capture budget for the mission, however, requires SDO to avoid frequent thruster maneuvers, while concerns about on-orbit jitter restrict the maximum desired wheel speeds desired from the RWAs. The plan for on-orbit wheel speed and momentum management will be discussed as well as what is now being done in operation after the jitter environment was characterized. The SDO ACS hardware complement is single-fault tolerant. Two main processors carry virtually identical copies of the command and data handling and ACS software, and two identical attitude control electronics (ACE) boxes carry Coldfire processors with contingency ACS software and other hardware interface cards; the ACE structure allows reaction wheels to be commanded by the Sun-pointing Safehold independent of the Mil Std 1553 data bus. The sixteen Adcole CSSs are grouped into primary and backup sets of eight sensors, each set providing the ability to calculate a sun vector. Each set of eight eyes provides full 4 -steradian coverage. The Adcole DSS comprises an optics head and a separate electronics box providing a 1553 data interface. The electronics box is mounted inside the Faraday cage created by the spacecraft bus module. The DSS head with its 32- deg square FOV is mounted on the instrument module with its boresight along the spacecraft X axis, nearly aligned with the Sun during observations. Adcole has designed the DSS calibration parameters so that the accuracy is 0.24 arcminutes within 10 deg of the boresight, and diminishes to 3 arcminutes as the Sun moves towards the edges of its FOV . This DSS calibration scheme provides higher accuracy attitude determination over the range of the instrument calibration maneuvers.

Morgenstern, Wendy M.↗

Guidance, Navigation, and Control Considerations for Nuclear Thermal Propulsion

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation NTP system could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. The role of a first generation NTP in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progress made under the NTP project could also help enable high performance fission power systems and Nuclear Electric Propulsion (NEP). Guidance, navigation, and control of NTP may have some unique but manageable characteristics.

Houts, Michael G.↗

Guidance, Navigation and Control (GN and C) Design Overview and Flight Test Results from NASA's Max Launch Abort System (MLAS)

The National Aeronautics and Space Administration Engineering and Safety Center designed, developed and flew the alternative Max Launch Abort System (MLAS) as risk mitigation for the baseline Orion spacecraft launch abort system already in development. The NESC was tasked with both formulating a conceptual objective system design of this alternative MLAS as well as demonstrating this concept with a simulated pad abort flight test. Less than 2 years after Project start the MLAS simulated pad abort flight test was successfully conducted from Wallops Island on July 8, 2009. The entire flight test duration was 88 seconds during which time multiple staging events were performed and nine separate critically timed parachute deployments occurred as scheduled. This paper provides an overview of the guidance navigation and control technical approaches employed on this rapid prototyping activity; describes the methodology used to design the MLAS flight test vehicle; and lessons that were learned during this rapid prototyping project are also summarized.

Dennehy, Cornelius J.↗

Lunar Reconnaissance Orbiter (LRO) Guidance, Navigation and Control (GN&C) Overview

The National Aeronautics and Space Administration s (NASA) Lunar Reconnaissance Orbiter (LRO) launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle and into a direct insertion trajectory to the oon. LRO, which was designed, built, and operated by the NASA Goddard Space Flight Center in Greenbelt, MD, is gathering crucial data on the lunar environment that will help astronauts prepare for long-duration lunar expeditions. The mission has a nominal life of 1 year as its seven instruments find safe landing sites, locate potential resources, characterize the radiation environment, and test new technology. To date, LRO has been operating well within the bounds of its requirements and has been collecting excellent science data images taken from the LRO Camera Narrow Angle Camera of the Apollo landing sites appeared on cable news networks. A significant amount of information on LRO s science instruments is provided at the LRO mission webpage. LRO s Guidance, Navigation and Control (GN&C) subsystem is made up of an onboard attitude control system (ACS) and a hardware suite of sensors and actuators. The LRO onboard ACS is a collection of algorithms based on high level and derived requirements, and reflect the science and operational events throughout the mission lifetime. The primary control mode is the Observing mode, which maintains the lunar pointing orientation and any offset pointing from this baseline. It is within this mode that all science instrument calibrations, slews and science data is collected. Because of a high accuracy requirement for knowledge and pointing, the Observing mode makes use of star tracker (ST) measurement data to determine an instantaneous attitude pointing. But even the star trackers alone do not meet the tight requirements, so a six-state Kalman Filter is employed to improve the noisy measurement data. The Observing mode obtains its rate information from an inertial reference unit (IRU) and in the event of an IRU failure, the rate data is be derived from the star tracker, but with degraded pointing performance. The Delta-V control mode responsibility is to maintain attitude pointing during the cruise trajectory, insertion burns and lunar orbit maintenance by adjustments made to the spacecraft s velocity magnitude and vector direction. The ACS also provides for a thruster based system momentum management algorithm (known as Delta-H) to maintain the system and wheel momentum to within acceptable levels. In the event an anomaly causes the LRO spacecraft to lose the ability to maintain its current attitude pointing, a Sun Safe mode is included in the ACS for the purpose of providing a known power and thermally safe coarse inertial sun attitude for an indefinite period of time, within the manageable limits of the reaction wheels. The Sun Safe mode is also the initial spacecraft control mode off of the launch vehicle and provides for a means to null tip-off rates immediately after separation. The nominal configuration is to use the IRU for rate information in the controller. In the event of a gyro failure a gyroless control mode was developed that computes rate information from the CSS data.

Garrick, Joseph↗

Terminal area automatic navigation, guidance, and control 1: Automatic rollout, turnoff, and taxis

A study developed for the TCV B-737, designed to apply existing navigation aids plus magnetic leader cable signals and develop breaking and reverse thrust guidance laws to provide for rapid automated rollout, turnoff, and taxi to reduce runway occupation time for a wide variety of landing conditions for conventional commercial-type aircraft, is described. Closed loop guidance laws for braking and reverse thrust are derived for rollout, turnoff, and taxi, as functions of the landing speed, the desired taxi speed and the distance to go. Brake limitations for wet runway conditions and reverse thrust limitations are taken into account to provide decision rules to avoid tire skid and to choose an alternate turnoff point, farther down the runway, to accommodate extreme landing conditions.

Pines, S.↗

Advanced information processing system: Hosting of advanced guidance, navigation and control algorithms on AIPS using ASTER

This program demonstrated the integration of a number of technologies that can increase the availability and reliability of launch vehicles while lowering costs. Availability is increased with an advanced guidance algorithm that adapts trajectories in real-time. Reliability is increased with fault-tolerant computers and communication protocols. Costs are reduced by automatically generating code and documentation. This program was realized through the cooperative efforts of academia, industry, and government. The NASA-LaRC coordinated the effort, while Draper performed the integration. Georgia Institute of Technology supplied a weak Hamiltonian finite element method for optimal control problems. Martin Marietta used MATLAB to apply this method to a launch vehicle (FENOC). Draper supplied the fault-tolerant computing and software automation technology. The fault-tolerant technology includes sequential and parallel fault-tolerant processors (FTP & FTPP) and authentication protocols (AP) for communication. Fault-tolerant technology was incrementally incorporated. Development culminated with a heterogeneous network of workstations and fault-tolerant computers using AP. Draper's software automation system, ASTER, was used to specify a static guidance system based on FENOC, navigation, flight control (GN&C), models, and the interface to a user interface for mission control. ASTER generated Ada code for GN&C and C code for models. An algebraic transform engine (ATE) was developed to automatically translate MATLAB scripts into ASTER.

Brenner, Richard↗

Simple Sensitivity Analysis for Orion Guidance Navigation and Control

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch. We describe in this paper a sensitivity analysis tool ("Critical Factors Tool" or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Pressburger, Tom↗

Apollo 16 mission Report. Supplement 1: Apollo 16 guidance, navigation, and control system performance analysis report

The results are reported of additional studies which were conducted to supplement conclusions drawn in the MSC Mission Report and analyses which were not completed in time to meet the Mission Report dealine. A detailed evaluation of the Abort Guidance System sensor assembly and results from the investigation of the X gyro loop anomaly are included. Further evidence is presented substantiating the excellent LM IMU performance obtained from preliminary indications. A detailed study is presented of the procedural changes implemented on Apollo 16 to diminish the number and duration of interruptions to the CSM DAP attitude maneuver during P20 Option 5 operations.

Source record↗

Navigation, guidance, and control systems for V/STOL aircraft.

The development of digital autopilots and integrated avionics systems, applicable to many classes of vehicles and missions, was undertaken by Sperry Flight Systems in the mid-sixties. The first application of the system was planned for automatic flight control in the U.S. supersonic transport; the termination of that program, however, thwarted any flight experience. The second application, which has additional navigation and energy management functions, is an airborne simulator of the space shuttle vehicle. The latter system underwent a series of successful flight tests in a CV-990 aircraft under contract with NASA. The third application, which has new electronic displays, air data computation, and time-constrained guidance (i.e., specified position and altitude at a specified time), is in the DOT/NASA STOLAND test program. The STOLAND system is described specifically in this paper.

Osder, S. S.↗

Autonomous RPRV Navigation, Guidance and Control

Dryden Flight Research Center has the responsibility for flight testing of advanced remotely piloted research vehicles (RPRV) to explore highly maneuverable aircraft technology, and to test advanced structural concepts, and related aeronautical technologies which can yield important research results with significant cost benefits. The primary purpose is to provide the preliminary design of an upgraded automatic approach and landing control system and flight director display to improve landing performance and reduce pilot workload. A secondary purpose is to determine the feasibility of an onboard autonomous navigation, orbit, and landing capability for safe vehicle recovery in the event of loss of telemetry uplink communication with the vehicles. The current RPRV approach and landing method, the proposed automatic and manual approach and autoland system, and an autonomous navigation, orbit, and landing system concept which is based on existing operational technology are described.

Johnston, Donald E.↗