Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “GUIDANCE”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47

L2 Earth Atmosphere Observatory: Formation Guidance, Metrology and Control Synthesis

The Earth Observatory Formation at L2, a Lagrange libration point, is a unique large aperture (25 m diameter) space telescope concept that will improve the knowledge and understanding of dynamic, chemical and radiative mechanisms that cause changes in the atmosphere, and can lead to the development of models and techniques to predict short and long-term climate changes. The results of this concept definition study show that the telescope concept is feasible, and can have technology readiness in the 2020 time frame. Further advanced development in several subsystems is needed, such as higher efficiency Xenon ion thrusters with throttling, and optical quality large membrane mirror with active shape control. It presents an analysis and solution of guidance, sensing, control, and propulsion problems for a formation of two spacecraft on the Sun-Earth line in the neighborhood of the Sun-Earth L2 point, that observes Earth s atmosphere during continuous solar occultation by the Earth. A system architecture is described for the observatory, and its components that include unique mission specific metrology. The formation must follow a powered trajectory with strictly limited fuel use to observe solar occultation. A configuration of ion thrusters and reaction wheels for translation and attitude control is designed along with algorithms for orbit following and formation control. Simulation results of the orbital and formation dynamics are presented that verify performance of the control systems.

Earth Atmosphere Observatory Formation↗

Guidance, Navigation, and Control Performance for the GOES-R Spacecraft

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites, scheduled for delivery in late 2015 and launch in early 2016. Relative to the current generation of GOES satellites, GOES-R represents a dramatic increase in Earth and solar weather observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations. GOES-R will also provide unprecedented availability, with less than 120 minutes per year of lost observation time. The Guidance Navigation & Control (GN&C) design requirements to achieve these expanded capabilities are extremely demanding. This paper first presents the pointing control, pointing stability, attitude knowledge, and orbit knowledge requirements necessary to realize the ambitious Image Navigation and Registration (INR) objectives of GOES-R. Because the GOES-R suite of instruments is sensitive to disturbances over a broad spectral range, a high fidelity simulation of the vehicle has been created with modal content over 500 Hz to assess the pointing stability requirements. Simulation results are presented showing acceleration, shock response spectrum (SRS), and line of sight responses for various disturbances from 0 Hz to 512 Hz. These disturbances include gimbal motion, reaction wheel disturbances, thruster firings for station keeping and momentum management, and internal instrument disturbances. Simulation results demonstrate excellent performance relative to the pointing and pointing stability requirements, with line of sight jitter of the isolated instrument platform of approximately 1 micro-rad. Low frequency motion of the isolated instrument platform is internally compensated within the primary instrument. Attitude knowledge and rate are provided directly to the instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The allowable IRE ranges from 1 to 18.5 micro-rad, depending upon the time window of interest. The final piece of the INR performance is orbit knowledge. Extremely accurate orbital position is achieved by GPS navigation at Geosynchronous Earth Orbit (GEO). Performance results are shown demonstrating compliance with the 50 to 75 m orbit position accuracy requirements of GOES-R, including during station-keeping and momentum management maneuvers. As shown in this paper, the GN&C performance for the GOES-R series of spacecraft supports the challenging mission objectives of the next generation GEO Earth-observation satellites.

Guidance↗

Fuel-Efficient Descent and Landing Guidance Logic for a Safe Lunar Touchdown

The landing of a crewed lunar lander on the surface of the Moon will be the climax of any Moon mission. At touchdown, the landing mechanism must absorb the load imparted on the lander due to the vertical component of the lander's touchdown velocity. Also, a large horizontal velocity must be avoided because it could cause the lander to tip over, risking the life of the crew. To be conservative, the worst-case lander's touchdown velocity is always assumed in designing the landing mechanism, making it very heavy. Fuel-optimal guidance algorithms for soft planetary landing have been studied extensively. In most of these studies, the lander is constrained to touchdown with zero velocity. With bounds imposed on the magnitude of the engine thrust, the optimal control solutions typically have a "bang-bang" thrust profile: the thrust magnitude "bangs" instantaneously between its maximum and minimum magnitudes. But the descent engine might not be able to throttle between its extremes instantaneously. There is also a concern about the acceptability of "bang-bang" control to the crew. In our study, the optimal control of a lander is formulated with a cost function that penalizes both the touchdown velocity and the fuel cost of the descent engine. In this formulation, there is not a requirement to achieve a zero touchdown velocity. Only a touchdown velocity that is consistent with the capability of the landing gear design is required. Also, since the nominal throttle level for the terminal descent sub-phase is well below the peak engine thrust, no bound on the engine thrust is used in our formulated problem. Instead of bangbang type solution, the optimal thrust generated is a continuous function of time. With this formulation, we can easily derive analytical expressions for the optimal thrust vector, touchdown velocity components, and other system variables. These expressions provide insights into the "physics" of the optimal landing and terminal descent maneuver. These insights could help engineers to achieve a better "balance" between the conflicting needs of achieving a safe touchdown velocity, a low-weight landing mechanism, low engine fuel cost, and other design goals. In comparing the computed optimal control results with the preflight landing trajectory design of the Apollo-11 mission, we noted interesting similarities between the two missions.

guidance logic↗

Explicit Low-Thrust Guidance for Reference Orbit Targeting

The problem of a low-thrust spacecraft controlled to a reference orbit is addressed in this paper. A simple and explicit low-thrust guidance scheme with constrained thrust magnitude is developed by combining the fundamental equations of motion for constrained systems from analytical dynamics with a Lyapunov-based method. Examples are given for a spacecraft controlled to a reference trajectory in the circular restricted three body problem.

low-thrust guidance↗

Kepler Fine Guidance Sensor Data

The Kepler and K2 missions collected Fine Guidance Sensor (FGS) data in addition to the science data, as discussed in the Kepler Instrument Handbook (KIH, Van Cleve and Caldwell 2016). The FGS CCDs are frame transfer devices (KIH Table 7) located in the corners of the Kepler focal plane (KIH Figure 24), which are read out 10 times every second. The FGS data are being made available to the user community for scientific analysis as flux and centroid time series, along with a limited number of FGS full frame images which may be useful for constructing a World Coordinate System (WCS) or otherwise putting the time series data in context. This document will describe the data content and file format, and give example MATLAB scripts to read the time series. There are three file types delivered as the FGS data.1. Flux and Centroid (FLC) data: time series of star signal and centroid data. 2. Ancillary FGS Reference (AFR) data: catalog of information about the observed stars in the FLC data. 3. FGS Full-Frame Image (FGI) data: full-frame image snapshots of the FGS CCDs.

Kepler↗

Fine Guidance Sensor Data

The Kepler and K2 missions collected Fine Guidance Sensor (FGS) data in addition to the science data, as discussed in the Kepler Instrument Handbook (KIH, Van Cleve and Caldwell 2016). The FGS CCDs areframe transfer devices located in the corners of the Kepler focal plane, which are read out 10 times every second. The FGS data are being made available to the user community for scientific analysis as flux and centroid time series, along with a limited number of FGS full frame images which may be useful for constructing a World Coordinate System (WCS) or otherwise putting the time series data in context. This document will describe the data content and file format, and give example MATLAB scripts to read the time series.

FGS↗

Human Landing System Storable Propellant Architecture: Mission Design, Guidance, Navigation, and Control

In preparation of the NextSTEP-2 Appendix H awards, NASA’s Human Landing System (HLS) Program (HLSP) went through an abbreviated Design Analysis Cycle (DAC), or miniDAC, to characterize and quantify how a storable propellant design would affect and improve overall system performance of the Government reference design. As part of that miniDAC, HLSP ran multiple trade studies and assessments, including aspects of Mission Design, Flight Mechanics (FM), and Guidance, Navigation, and Control (GN&C). The storable propellant designs were assessed through the baseline mission targeting the Near Rectilinear Halo Orbit (NRHO) and several alternate staging orbits. This paper focuses on the FM and GN&C trades and assessments completed as part of the miniDAC as well as the GN\&C elements of the miniDAC Master Equipment List (MEL) developed for the storable propellant lander configurations.

Landers↗

Best Practices for the Design, Development, and Operation of Robust and Reliable Space Vehicle Guidance, Navigation, and Control Systems

This document summarizes and updates the NESC Guidance, Navigation, and Control (GN&C) Technical Discipline Team’s (TDT) work to synthesize and document the current best practices for the design & development of robust and reliable GN&C systems for robotic and crewed (human-rated) spacecraft. These GN&C best practices for future science and exploration missions were derived from the lessons learned, both positive and negative, on earlier spaceflight projects, both robotic and crewed. An attempt has been made to capture preferred practices that reflect the key considerations, trades, and processes directly attributed to past mission success.

Guidance, Navigation, and Control↗

Guidance and Control for Laser-Based Non-Cooperative Target Detumbling

Large pieces of orbital debris form a significant risk of fragmentation in case of collision. Such fragmentation would greatly increase the number of trackable and untrackable debris on orbit. This makes them attractive targets for future rendezvous and disposal missions. However, these non-cooperative targets tend to be tumbling and rendezvous with them is a dangerous prospect. To avoid this danger, contactless detumbling through laser ablation has been proposed prior to rendezvous. Existing proposals for contactless laser-based detumbling have yet to include an in-depth study of the problem's guidance, navigation, and control requirements. In this work we develop an attitude and relative motion control scheme for a chaser satellite detumbling a non-cooperative target via laser. We show that detumbling can be achieved with reasonable time and dV budgets. With Monte Carlo methods we explore the impact of laser force on the detumbling operation and reveal some non-intuitive relationships.

Guidance↗

Guidance and Control for Laser-Based Non-Cooperative Target Detumbling

Large pieces of orbital debris form a significant risk of fragmentation in case of collision. Such fragmentation would greatly increase the number of trackable and untrackable debris on orbit. This makes them attractive targets for future rendezvous and disposal missions. However, these non-cooperative targets tend to be tumbling and rendezvous with them is a dangerous prospect. To avoid this danger, contactless detumbling through laser ablation has been proposed prior to rendezvous. Existing proposals for contactless laser-based detumbling have yet to include an in-depth study of the problem's guidance, navigation, and control requirements. In this work we develop an attitude and relative motion control scheme for a chaser satellite detumbling a non-cooperative target via laser. We show that detumbling can be achieved with reasonable time and dV budgets. With Monte Carlo methods we explore the impact of laser force on the detumbling operation and reveal some non-intuitive relationships.

Guidance↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of A Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

A Physics-Based Work-Energy Formulation for Real-Time Trajectory Guidance of a Lunar Lander

Throughout the years, many researchers have calculated and optimized trajectory solutions for lunar landing systems by employing sophisticated mathematical methods, that include: Hamilton’s Principle of Variation, Pontryagin’s maximum principle, and well known convex-optimization techniques among others. Many of these approaches typically require expensive computational resources to achieve convergence in the solution. In an effort to reduce complexity and the computational load required to obtain real-time guidance commands, a simple physics-based work-energy approach has been formulated. This approach is based on the dissipation of the mechanical energy of the vehicle to its final desired energy state required to achieve a safe landing. The rocket engine(s) employed during landing (among other maneuvers) dissipates mechanical energy by both doing work against the velocity vector of the vehicle (thus defining the trajectory path), and by jettisoning mass. Therefore, by solving the energy dissipation problem at every step of the maneuver, a much simpler formulation that naturally and quickly attains convergence is obtained. This formulation is not limited to approach, landing, and divert maneuvers, but in principle it can be employed during de-orbiting, braking burn, ascent, as well as orbit insertion.

Guidance↗

Entry Guidance Design and Post-Flight Performance of the Mars 2020 Mission

Like its predecessor Mars Science Laboratory, the Mars 2020 mission successfully utilized a derivative of the Apollo Entry Terminal Point Controller guidance algorithm, whereby bank angle controls range flown along a trajectory. The flight performance of this algorithm in conjunction with a range-trigger for parachute deploy delivered the Perseverance rover to 1.7 km from the expected touchdown location within an ellipse of 7.5 x 5.2 km. This miss distance is largely attributed to atmospheric and aerodynamic modeling uncertainties between the design and as-flown trajectory. This algorithm for guided entry continues to provide a solid basis for Mars missions to improve upon.

Guidance↗

Post-Flight EDL Entry Guidance for the Mars 2020 Mission

Like its predecessor Mars Science Laboratory, the Mars 2020 mission successfully utilized a derivative of the Apollo Entry Terminal Point Controller guidance algorithm, whereby bank angle controls range flown along a trajectory. The flight performance of this algorithm in conjunction with a range-trigger for parachute deploy delivered the Perseverance rover to 1.7 km from the expected touchdown location within an ellipse of 7.5 x 5.2 km. This miss distance is largely attributed to atmospheric and aerodynamic modeling uncertainties between the design and as-flown trajectory. This algorithm for guided entry continues to provide a solid basis for Mars missions to improve upon.

Guidance↗

Remote Guidance of a Mothership-Daughtership Formation for Asteroid Exploration

This work presents an application of Model Predictive Control to maintain long-term stability for a three-satellite formation around the asteroid Apophis via remote guidance. The mothership and two daughterships perform tomographic characterization with a bistatic radar. The mothership estimates the states of all three spacecraft and determines the necessary control to maintain the desired antipodal daughtership states. An Extended Kalman Filter estimates the mothership states. A Batch Least Squares algorithm estimates the daughtership states and performs maneuver reconstruction for the mothership-administered thrust commands under thruster and gravitational uncertainty. The formulation maintains the antipodal angle with growing instability amidst these uncertainties.

Guidance↗