Suboptimal filtering. Part 4 - Test-bed computer program Final report
Computer program plan for simulating real time observation schedules and combined effects of dynamic model errors in three-dimensional satellite motion
Bailie, A. E.↗
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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.
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Design of an all-attitude flight control system to execute commanded bank angles and angles of attack
A flight control system for use in air-to-air combat simulation was designed. The input to the flight control system are commanded bank angle and angle of attack, the output are commands to the control surface actuators such that the commanded values will be achieved in near minimum time and sideslip is controlled to remain small. For the longitudinal direction, a conventional linear control system with gains scheduled as a function of dynamic pressure is employed. For the lateral direction, a novel control system, consisting of a linear portion for small bank angle errors and a bang-bang control system for large errors and error rates is employed.
Burgin, G. H.↗
CHIMERA II - A real-time multiprocessing environment for sensor-based robot control
A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.
Stewart, David B.↗
Application of nonlinear feedback control theory to supermaneuverable aircraft
Controlled flight at extremely high angles of attack, far exceeding the stall angle, and/or at high angular rates is sometimes referred to as supermaneuvering flight. The objective was to examine methods for design of control laws for aircraft performing supermaneuvers. Since the equations which govern the motion of aircraft during supermaneuvers are nonlinear, this study concentrated on nonlinear control law design procedures. The two nonlinear techniques considered were Nonlinear Quadratic Regulator (NLQR) theory and nonlinear dynamic inversion. A conventional gain scheduled proportional plus integral (P + I) controller was also developed to serve as a baseline design typical of current control laws used in aircraft. A mathematical model of a generic supermaneuverable aircraft was developed from data obtained from the literature. A detailed computer simulation of the aircraft was also developed. This simulation allowed the flying of proposed supermaneuvers and was used to evaluate the performance of the control law designs and to generate linearized models of the aircraft at different flight conditions.
Garrard, William L.↗
STS-109 Flight Day 2 Highlights
Footage shows the cargo bay of the Columbia Orbiter, including the rigid array carrier, the solar arrays to be installed on the Hubble Space Telescope, and the robotic arm. Close-up shots show several components of the flight support system. STS-109 Commander Scott Altman, Payload Commander John Grunsfeld, and Mission Specialist Nancy Currie are seen on the flight deck, and they answer questions about the stabilization of the freon flow, details of the upcoming rendezvous and capture of the Hubble Space Telescope, the scheduled spacewalks, and the social dynamics of the flight crew.
Source record↗
Progress Towards the Solar Dynamics Observatory
The Solar Dynamics Observatory, or SDO, is scheduled to be the first mission to launch in 2007 under the new Living With a Star (LWS) program. It builds on the success of SOHO and other recent solar missions, but will observe the Sun at greater resolution and faster time cadence with a set of remote sensing instruments generating data in excess of 100 megabytes per second. The Science Definition Team produced a report consisting of a series of science objectives and a baseline instrument complement. Instrument proposals were due in April 2002, with selection to occur in the late summer of 2002. The spacecraft is being built at NASA Goddard Spacecraft Center by a team of engineers which are currently undergoing the formulation process. The presentation will discuss the current status of the science investigation selection and the spacecraft formulation.
Thompson, B. J.↗
Data-Driven Security Assessment of Power Grids Based on Machine Learning Approach: Preprint
Data-driven security assessment provides key indicators on power system stability using simulations on scheduling models, as opposed to dynamic simulations that are more time-consuming. This paper investigates data-driven security assessment of power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm due to its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool, including transient stability, frequency stability and small signal stability. The estimation values from machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the three stability metrics.
14 SOLAR ENERGY↗
A direct transcription-based multiple shooting formulation for dynamic optimization
The growing need for fast and efficient solution techniques for solving dynamic optimization problems is driven by a broad spectrum of applications in scheduling and control. We suggest a novel framework for dynamic optimization that utilizes a multiple shooting “backbone” with discrete rather than continuous subproblems, thereby eliminating need for repeated time-integration. A Lagrangian relaxation (LR)-based decomposition scheme is proposed, which dualizes the state continuity requirements between subproblems and enables parallel solution of the problem. We demonstrate the applicability of our method on two case studies: the Van der Pol oscillator and a batch reactor.
42 ENGINEERING↗
LACE flight dynamics experiment
The Low Power Atmospheric Compensation Experiment (LACE) is scheduled for launch in late 1989 into a 556 km altitude circular orbit of 43 deg inclination. The LACE flight dynamics experiment is an experiment secondary to the primary LACE mission. The purpose of the experiment is to provide on-orbit systems identification of the LACE spacecraft. The structure of the LACE spacecraft is of special interest to the CSI community. It incorporates 3 deployable/retractable booms of maximum length 45.72 m (150 ft) mounted on a rectangular parallelepiped bus of mass 1,200 kg. The zenith directed gravity gradient boom is mounted on the top of the bus; the retroreflector boom is mounted forward and deployed along the velocity vector, the balance boom is mounted and pointed aft. Attitude stabilization is accomplished by means of gravity gradient torques and by a momentum wheel. The LACE flight dynamics experiment is designed to measure modal frequencies, damping ratios, and oscillation amplitudes of the LACE spacecraft, as well as the vibration intensity generated by boom deployments and retractions. It is anticipated that this experiment will provide an opportunity for improvements in the accuracy of computer simulations of flexible structures and multibody dynamics.
Fisher, Shalom↗
Optimal scheduling for profit maximization of energy storage merchants considering market impact based on dynamic programming
This paper analyzes how electricity merchants' market impact affects merchants' profit. Energy storage has long been studied for its role in maximizing profit, and merchant decisions are assumed to have no impact on market prices. However, the trading decisions of large-scale energy storage merchants (e.g., pumped storage hydro) will affect the market prices. This paper employs dynamic programming theory to investigate merchants' optimal economic dispatch considering the market impact and physical characteristics of storage systems. Our findings show that the State-of-Charge (SOC) based analytical solution significantly facilitates energy storage merchants' decision-making. The SOC range is segmented into three regions by two optimal SOC reference points, which depend on the available energy in storage, given prices, and market impact. By comparing the current storage SOC with the reference points, the merchant can get the corresponding optimal actions. We analytically show that if the merchant neglects the market impact on the power market, she will exaggerate her expected profit when the price-taker and price-maker merchants have the same generating and pumping upper limits offered to Independent System Operators (ISOs). Furthermore, the profit-maximizing merchant must, therefore, assay to balance the trade-off correctly between the intensity of market impact and the dispatched power. Our findings are verified by numerical simulation, and results demonstrate the ramifications for electricity merchants in energy arbitrage decisions.
25 ENERGY STORAGE↗
Feasibility Study of a Multi Tilt-rotor Aircraft as the Artemis Lunar Training Vehicle
The Lunar Landing Research Vehicles (LLRVs) and the Lunar Landing Training Vehicles (LLTVs) provided astronaut candidates for the Apollo program with essential experience and confidence required to complete the missions, and contributed to six successful manned landings on the moon. The primary challenge in terrestrial training was being able to replicate the ratio of bank angle to linear acceleration that a pilot would experience in lunar gravity. Presently, as the Artemis program seeks to return humans to the Moon by 2025, engineers are evaluating suitable platforms to serve as an In-Flight Trainer (IFT) or Artemis Lunar Training Vehicle (ALTV) for astronauts training in the task of manual landing. The program is investigating the viability of current technology in the field of electric vertical takeoff and landing (eVTOL) vehicles and is evaluating using a multi tilt-rotor aircraft platform as a candidate platform for a preliminary ALTV. The tilt-rotor capability enables the vehicle attitude to be decoupled from its flight path, which is a crucial requirement in realistically simulating lunar gravity on Earth. Other key considerations include compensating for a lack of aerodynamic forces while flying through the atmosphere of Earth, as well as the ability to simulate the dynamics of multiple different lander designs for the Human Landing System (HLS) program. This paper details the feasibility study and presents a preliminary flight control architecture for an IFT based on a notional multi tilt-rotor platform. The modeling-following control law, based on nonlinear dynamic inversion (NDI), removes the need for gain scheduling because the vehicle operates across a wide range of flight conditions. The inner-loop dynamic control allocation strategy consists of a static portion that is optimized offline for trim while compensating for the difference in gravity and a dynamic portion that is computed in real time. The reference model consists of the full closed-loop dynamics of a generic HLS design. The modularity of the flight control architecture enables evaluation of multiple HLS concepts with minimal modifications to the control law. Simulation results of the multi tilt-rotor configuration following the final portion of the Apollo 11 descent trajectory are shown.
Jing Pei↗
Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem
The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, the incorporation of differential equations that govern the system dynamics makes DED an optimization problem that is computationally prohibitive to solve. In this work, we present a new data-driven approach based on differentiable programming to efficiently obtain offline parametric solutions to the underlying DED problem. In particular, we employ the recently proposed differentiable predictive control (DPC) for offline learning of explicit neural control policies based on identified Koopman operator (KO) model of the system dynamics. We demonstrate the high solution quality and five orders of magnitude computational-time savings of the DPC method over the original optimization-based DED approach on a 9-bus test power grid network.
King, Ethan↗
Solving the Dynamics-Aware Economic Dispatch Problem with the Koopman Operator
The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, in contrast to T-ED, DED is a nonlinear, non-convex optimization problem that is computationally prohibitive to solve. We introduce a machine learning-based operator-theoretic approach for solving the DED problem efficiently. Specifically, we develop a novel discrete-time Koopman Operator (KO) formulation that embeds domain information into the structure of the KO to learn high-fidelity approximations of the generator dynamics. Using the KO approximation, the DED problem can be reformulated as a computationally tractable linear program (abbreviated DED-KO). We demonstrate the high solution quality and computational-time savings of the DED-KO model over the original DED formulation on a 9-bus test system.
King, Ethan↗
EJFAT: Towards Intelligent Compute Destination Load Balancing
To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.
Lawrence, David↗
Shared Activity Coordination
Interacting agents that interleave planning and execution must reach consensus on their commitments to each other. In domains where agents have varying degrees of interaction and different constraints on communication and computation, agents will require different coordination protocols in order to efficiently reach consensus in real time. We briefly describe a largely unexplored class of real-time, distributed planning problems (inspired by interacting spacecraft missions), new challenges they pose, and a general approach to solving the problems. These problems involve self-interested agents that have infrequent communication but collaborate on joint activities. We describe a Shared Activity Coordination (SHAC) framework that provides a decentralized algorithm for negotiating the scheduling of shared activities in a dynamic environment, a soft, real-time approach to reaching consensus during execution with limited communication, and a foundation for customizing protocols for negotiating planner interactions. We apply SHAC to a realistic simulation of interacting Mars missions and illustrate the simplicity of protocol development.
coordination↗
Open-Loop Pitch Table Optimization for the Maximum Dynamic Pressure Orion Abort Flight Test
NASA has scheduled the retirement of the space shuttle orbiter fleet at the end of 2010. The Constellation program was created to develop the next generation of human spaceflight vehicles and launch vehicles, known as Orion and Ares respectively. The Orion vehicle is a return to the capsule configuration that was used in the Mercury, Gemini, and Apollo programs. This configuration allows for the inclusion of an abort system that safely removes the capsule from the booster in the event of a failure on launch. The Flight Test Office at NASA's Dryden Flight Research Center has been tasked with the flight testing of the abort system to ensure proper functionality and safety. The abort system will be tested in various scenarios to approximate the conditions encountered during an actual Orion launch. Every abort will have a closed-loop controller with an open-loop backup that will direct the vehicle during the abort. In order to provide the best fit for the desired total angle of attack profile with the open-loop pitch table, the table is tuned using simulated abort trajectories. A pitch table optimization program was created to tune the trajectories in an automated fashion. The program development was divided into three phases. Phase 1 used only the simulated nominal run to tune the open-loop pitch table. Phase 2 used the simulated nominal and three simulated off nominal runs to tune the open-loop pitch table. Phase 3 used the simulated nominal and sixteen simulated off nominal runs to tune the open-loop pitch table. The optimization program allowed for a quicker and more accurate fit to the desired profile as well as allowing for expanded resolution of the pitch table.
Stillwater, Ryan A.↗
Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights
One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.
Chatzimavroudis, George P.↗
Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling
Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, whereas uncoordinated assignments deliver just 58% of travelers in time.
33 ADVANCED PROPULSION SYSTEMS↗